Dwight Read
Journal of Artificial Societies and Social Simulation 1 (1) 1

Kyeywords: Multi-Agent Simulation, Cultural Knowledge, Hunting and Gathering Societies
Abstract: The social boundaries of small scale human societies are defined through culturally defined kin relations that transcend the specifics of the genealogical relationships produced through procreation. Kinship knowledge is culturally defined, distributed knowledge that provides structure for the persons produced through demographic processes. However, the interplay between the demographic system and the cultural system has been difficult to model. Genealogical data are static and do not show how the vagaries of demographic processes affect implementation of a culturally defined, conceptual system. Demographic simulations can provide the dynamic dimension, but usually lack information on how the changing demographic makeup of a population affects application of culturally defined rules relating to marriage, reproduction, residence and the like. This paper presents results obtained from implementation of a multi-agent, demographically driven, simulation of a hunting and gathering group in which each agent is imbued with cultural knowledge that affects decisions to be made about marriage, reproduction and place of residence. The goal is to assess the implications of demographic processes, ego-centered decision making, and culturally determined structures (kin relations, social groupings and the like) for the resulting social system. Questions addressed in the simulation are based on ethnographic observations and it is shown that the simulation provides an effective means to assess the validity of hypotheses about the ethnographic observations.

Pietro Terna
Journal of Artificial Societies and Social Simulation 1 (2) 4

Kyeywords: Agent Based Models (ABM), Chaos, Intelligent Agents, Social Simulation, Swarm
Abstract: Social scientists are not computer scientists, but their skills in the field have to become better and better to cope with the growing field of social simulation and agent based modelling techniques. A way to reduce the weight of software development is to employ generalised agent development tools, accepting both the boundaries necessarily existing in the various packages and the subtle and dangerous differences existing in the concept of agent in computer science, artificial intelligence and social sciences. The choice of tools based on the object oriented paradigm that offer libraries of functions and graphic widgets is a good compromise. A product with this kind of capability is Swarm, developed at the Santa Fe Institute and freely available, under the terms of the GNU license. A small example of a model developed in Swarm is introduced, in order to show directly the possibilities arising from the use of these techniques, both as software libraries and methodological guidelines. With simple agents - interacting in a Swarm context to solve both memory and time simulation problems - we observe the emergence of chaotic sequences of transaction prices.

Troy J Strader, Fu-ren Lin and Michael J Shaw
Journal of Artificial Societies and Social Simulation 1 (2) 5

Kyeywords: Supply Chain Management, Multi-Agent Simulation, Swarm, Decision Support Systems, Electronic Commerce, Computer Industry, Electronics Industry
Abstract: Management of supply chains is a difficult task involving coordination and decision-making across organizational boundaries. Computational modeling using multi-agent simulation is a tool that can provide decision support for supply chain managers. We identify the components of a supply chain model and implement it in the Swarm multi-agent simulation platform. The model is used to study the impact of information sharing on order fulfillment in divergent assembly supply chains (commonly associated with the computer and electronics industries). We find that efficient information sharing enables inventory costs to be reduced while maintaining acceptable order fulfillment cycle times. This is true because information, which provides the basis for enhanced coordination and reduced uncertainty, can substitute for inventory.

Scott Moss
Journal of Artificial Societies and Social Simulation 1 (4) 1

Kyeywords: Crisis Management, Agent Cognition, Model Verification, Simulation Methodology
Abstract: The main purpose of this paper is to demonstrate an empirical approach to social simulation. The systems and the behaviour of middle-level managers of a real company are modelled. The managers' cognition is represented by problem space architectures drawn from cognitive science and an endorsements mechanism adapted from the literature on conflict resolution in rulebased systems. Both aspects of the representation of cognition are based on information provided by domain experts. Qualitative and numerical results accord with the views of domain experts.

David Hales
Journal of Artificial Societies and Social Simulation 1 (4) 2

Kyeywords: Artificial Societies, Computer Simulation, Memetics, Meta-Memes
Abstract: Using the "meme" conception (Dawkins 1976) of cultural transmission and computer simulations, an exploration is made of the relationship between agents, their beliefs about their environment, communication of those beliefs, and the global behaviours that emerge in a simple artificial society. This paper builds on previous work using the Minimeme model (Bura 1994). The model is extended to incorporate open-mindedness meta-memes (memes about memes). In the scenarios presented such meta-memes have dramatic effects, increasing the optimality of population distribution and the accuracy of existing beliefs. It is argued that artifical society experimentation offers a potentially fruitful response to the inherent problems of building new meme theory.

Steven Patrick, Patricia Dorman and Robert Marsh
Journal of Artificial Societies and Social Simulation 2 (1) 1

Kyeywords: Computer Simulation, Prison Management, Prison Riots, Organizational Control, Deterministic Systems, General Systems Theory
Abstract: Inmate group behavior is a complex phenomenon that many researchers have attempted to understand. Most of the individual theories applied to this issue have had limited success. This work uses computer simulation to apply a complex theory of organizational control to the issue of inmate group behavior that incorporates all the major theoretical components found in the individual theories. The complete theory is first presented and then basic simulation results are discussed. The findings show that the simulated theory produced results that are empirically realistic. The control processes used by prisons generally produce compliance from inmates but these same control processes result in episodic periods of negative inmate group behavior. These initial results point to the promise of computer simulation for understanding complex control issues in ways simpler theories cannot.

Nicole J. Saam and Andreas G. Harrer
Journal of Artificial Societies and Social Simulation 2 (1) 2

Kyeywords: Simulation of Norms, Social Inequality, Functions of Norms
Abstract: In this paper, we compare the computational and sociological study of norms, and resimulate previous simulations (Conte and Castelfranchi 1995a, Castelfranchi, Conte and Paolucci 1998) under slightly different conditions. First, we analyze the relation between norms, social inequality and functional change more closely. Due to our results, the hypothesis stating that the "finder-keeper" norm while controlling aggression efficaciously reduces social inequality holds only in quite egalitarian societies. Throughout a variety of inegalitarian societies, it instead increases social inequality. This argument which can be traced back to Marx is being investigated by use of computer simulations of artificial societies. Second, we remodel normative behaviour from a sociological point of view by implementing Haferkamp's theory of action approach to deviant behaviour. Following the game theoretic models, the computational study of norms has up to now ignored the importance of power in explaining how norms affect social behaviour, how norms emerge, become established and internalized, and change. By simulating Haferkamp and repeating the Conte and Castelfranchi experiments, we demonstrate that it is possible to integrate power into computational models of norms.

Nigel Gilbert
Journal of Artificial Societies and Social Simulation 2 (1) 3

Kyeywords: Multi-Level Simulation, Social Simulation, Lisp, Computer Modelling, Social Simulation Tookit
Abstract: A package of Lisp functions is described which implements a simple multi-level simulation toolkit, MLS. Its design owes a great deal to MIMOSE. MLS runs within Lisp-Stat. It offers a set of functions, macros and objects designed to make the specification of multi-level models straightforward and easy to understand. Lisp-Stat provides a Lisp environment, statistical functions and easy to use graphics, such as histograms, scatterplots and spin-plots, to make the results of multi-level simulations easy to visualise.

Rosaria Conte and Scott Moss
Journal of Artificial Societies and Social Simulation 2 (1) 4

Kyeywords: Agent-Based Social Simulation, Special Interest Group, AgentLink
Abstract:

José Castro Caldas and Helder Coelho
Journal of Artificial Societies and Social Simulation 2 (2) 1

Kyeywords: Institutional Economics, Agent Modelling, Socio-Economic Simulation, Evolutionary Algorithms
Abstract: Institutions, the way they are related to the behaviour of the agents and to the aggregated performance of socio-economic systems, are the topic addressed by this essay. The research is based on a particular concept of a bounded rational agent living in society and by a population based simulation model that describes the processes of social learning. From simple co-ordination problems, where conventions spontaneously emerge, to situations of choice over alternative constitutional rules, simulation was used as a means to test the consistency and extract the implications of the models. Institutions, as solutions to recurring problems of social interaction, are both results and preconditions for social life, unintended outcomes and human devised constraints. In an evolutionary setting no support is found for the deep rooted beliefs about the 'naturally' beneficial outcomes generated by 'invisible-hand' processes or by any alternative Hobbesian meta-agency.

Cathy Small
Journal of Artificial Societies and Social Simulation 2 (3) 6

Kyeywords: Polynesia; Gender; Simulation
Abstract: A modeled Polynesian society is used to explain why, in Polynesia, growing stratification did not result in a devaluation of women's status, as most theorists would predict. The computer model used to explore this problem--called TongaSim--is a C++ program that attempts to emulate the basic social dynamics of Tonga, a Western Polynesian society. The program is capable of simulating the operation of a chiefdom with up to 100+ chiefly lines whose descendants marry and have children, create and maintain kinship relationships, exact and pay tribute, produce and redistribute agricultural wealth, expand in territory and go to war, and attempt to gain personal and group status. TongaSim was used to simulate the effect of warfare (a prime mover of stratification) on women's status, specifically the custom of "fahu" that asserts the spiritual superiority of sisters and sister's lines over brothers and their lines. Because of intermarriage patterns, this custom also serves to make higher status chiefly lines superior in kinship to lower status chiefly lines and, thus, supports traditional political power. Two simulations were conducted with the model--one with warfare OFF (inactivated) and one with warfare ON, allowing challenging lower chiefs to go to war and seize land if they were able to do so. The effect of warfare on the fahu custom and its implications in the virtual system were recorded and examined. The simulation showed that, despite the initial conflict between the interests of rising military chiefs and the fahu custom, the custom was appropriated by these rising chiefs, turning the fahu's political effects "on its head." Ultimately in the simulation, the fahu custom provided a vehicle for military chiefs to gain status and power. This, it is argued, is consistent with the lack of any historical evidence that the fahu was challenged and toppled during periods of growing warfare and stratification.

László Gulyás, Tamás Kozsik and John B. Corliss
Journal of Artificial Societies and Social Simulation 2 (3) 8

Kyeywords: Social Science Simulation, Agent-Based Modelling, Integrated Modelling Environment
Abstract: While computer models provide many advantages over traditional experimental methods, they also raise several problems. The process of software development is a complicated task with high potential for errors, especially when it is carried out by scientists holding their expertise in other fields than computer science. On the other hand, the process of creating computer simulations of social systems which reflect the reality of such systems requires insights considerably beyond expertise in computer science. The Multi-Agent Modelling Language (MAML) is one of the efforts to ease these difficulties. In its current version, MAML is a macro-language for Swarm (a freely distributed toolset under development at SFI), but it is also part of a larger Swarm-independent framework. Also, the design of MAML, while influenced by concepts from Swarm, is general enough to allow for later extension of the supported simulation kernels. This paper gives an overview of the mentioned larger framework, with special emphasis on MAML and its graphical CASE tool, the Model Design Interface.

Barry G. Lawson and Steve Park
Journal of Artificial Societies and Social Simulation 3 (1) 2

Kyeywords: Artificial Society, Discrete-Event Simulation, Synchronous Time Evolution, Simulation Artifacts, Asynchronous Time Evolution, Next-Event Simulation, Event List Processing
Abstract: "Artificial society" refers to an agent-based simulation model used to discover global social structures and collective behavior produced by simple local rules and interaction mechanisms. In most artificial society discrete-event simulation models, synchronous time evolution is used to drive the actions and interactions of the landscape and agents. Although for some applications synchronous time evolution is the correct modeling approach, other applications are better suited for asynchronous time evolution. In this paper we demonstrate that very different behavior can be observed in a typical artificial society model if agent events occur asynchronously. Using an adaptation of the artificial society model defined by Epstein and Axtell, we describe the implementation of asynchronous time evolution in a discrete-event simulation model. With output from this model, we show that the use of asynchronous time evolution can eliminate potential simulation artifacts produced using synchronous time evolution. Since the use of discrete-event simulation can produce an associated loss in computational performance, we also discuss means of improving the performance of the artificial society simulation model. We provide results demonstrating that acceptable computational performance for asynchronous time evolution can be achieved using an appropriate event list implementation.

Warren Thorngate
Journal of Artificial Societies and Social Simulation 3 (1) forum/1

Kyeywords: Simulation, Teaching, Social Processes, Programming Languages, Matlab
Abstract: Programming languages for social simulations are rapidly proliferating. The result is a Tower of Babel effect: Many of us find it increasingly effortful to learn and to teach more programming languages and increasingly difficult to sustain an audience beyond the programming dialect of our choice. We need a programming lingua franca. Here I argue why Matlab might be worth our consideration, especially to teach simulation programming techniques.

Chris Goldspink
Journal of Artificial Societies and Social Simulation 3 (2) 1

Kyeywords: Complex Systems, Autopoiesis, Social Simulation, Cognition, Agents, Modelling. Meta-Model, Ontology
Abstract: There is growing interest in extending complex systems approaches to the social sciences. This is apparent in the increasingly widespread literature and journals that deal with the topic and is being facilitated by adoption of multi-agent simulation in research. Much of this research uses simple agents to explore limited aspects of social behaviour. Incorporation of higher order capabilities such as cognition into agents has proven problematic. Influenced by AI approaches, where cognitive capability has been sought, it has commonly been attempted based on a 'representational' theory of cognition. This has proven computationally expensive and difficult to implement. There would be some benefit also in the development of a framework for social simulation research which provides a consistent set of assumptions applicable in different fields and which can be scaled to apply to simple and more complex simulation tasks. This paper sets out, as a basis for discussion, a meta-model incorporating an 'enactive' model of cognition drawing on both complex system insights and the theory of autopoiesis. It is intended to provide an ontology that avoids some of the limitation of more traditional approaches and at the same time providing a basis for simulation in a wide range of fields and pursuant of a wider range of human behaviours.

Peter Deadman, Edella Schlager and Randy Gimblett
Journal of Artificial Societies and Social Simulation 3 (2) 2

Kyeywords: Common Pool Resources, Intelligent Agents, Simulation, Bounded Rationality, Communication
Abstract: This paper describes the development of a series of intelligent agent simulations based on data from previously documented common pool resource (CPR) experiments. These simulations are employed to examine the effects of different institutional configurations and individual behavioral characteristics on group level performance in a commons dilemma. Intelligent agents were created to represent the actions of individuals in a CPR experiment. The agents possess a collection of heuristics and utilize a form of adaptation by credit assignment in which they select the heuristic that appears to yield the highest return under the current circumstances. These simulations allow the analyst to specify the precise initial configuration of an institution and an individual's behavioral characteristics, so as to observe the interaction of the two and the group level outcomes that emerge as a result. Simulations explore settings in which there is no communication between agents, as well as the relative effects on overall group behavior of two different communication routines. The behavior of these simulations is compared with documented CPR experiments. Future directions in the development of the technology are outlined for natural resource management modeling applications.

Joaquim Carvalho
Journal of Artificial Societies and Social Simulation 3 (3) forum/2

Kyeywords: Simulation, Teaching, User Interfaces to Agent Based Models
Abstract: The AgentSheets simulation software has been used for the last two years in a course for undergraduate students. The ease of use and extreme care put into the interface makes this tool a classroom success, allowing students to have hands-on experience of model construction without the overhead of learning complicated frameworks or programming languages. The limitations of the tool, in particular those that make difficult the construction of more complex models, are reviewed.

Juan de Lara Jaramillo and Manuel Alfonseca
Journal of Artificial Societies and Social Simulation 3 (4) 2

Kyeywords: Multi-Agent Systems, Agent-Based Simulation, Self-Organization, Language
Abstract: In this paper, we present several experiments of belief propagation in multi-agent communities. Each agent in the simulation has an initial random vocabulary (4 words) corresponding to each possible movement (north, south, east and west). Agents move and communicate the associated word to the surrounding agents, which can be convinced by the 'speaking agent', and change their corresponding word by 'imitation'. Vocabulary uniformity is achieved, but strong interactions and competition can occur between dominant words. Several moving and trusting strategies as well as agent roles are analyzed.

Alexander Staller and Paolo Petta
Journal of Artificial Societies and Social Simulation 4 (1) 2

Kyeywords: Social Norms, Appraisal Theory of Emotions ,Process Model of Emotions, Layered Agent Architecture, Simulation, JAM (BDI Agent Architecture), Micro-Macro Link, Aggression Control Case Study, Deontic Reasoning and Human Behaviour Models
Abstract: It is now generally recognised that emotions play an important functional role within both individuals and societies, thereby forming an important bond between these two levels of analysis. In particular, there is a bi-directional interrelationship between social norms and emotions, with emotions playing an instrumental role for the sustenance of social norms and social norms being an essential element of regulation in the individual emotional system. This paper lays the foundations for a computational study of this interrelationship, drawing upon the functional appraisal theory of emotions. We describe a first implementation of a situated agent architecture, TABASCOJAM, that incorporates a simple appraisal mechanism and report on its evaluation in a well-known scenario for the study of aggression control as a function of a norm, that was suitably extended. The simulation results reported in the original aggression control study were successfully reproduced, and consistent performances were achieved for extended scenarios with conditional norm obeyance. In conclusion, it is argued that the present effort indicates a promising lane towards the necessary abandonment of logical models for the explanation and simulation of human social behaviour.

Miles Parker
Journal of Artificial Societies and Social Simulation 4 (1) 5

Kyeywords: Agent-Based Simulation, Computer Modelling, Software Frameworks, Java
Abstract: Ascape is a framework designed to support the development, visualization, and exploration of agent based models. In this article I will argue that agent modeling tools and Ascape, in particular, can contribute significantly to the quality, creativity, and efficiency of social science simulation research efforts. Ascape is examined from the perspectives of use, design, and development. While Ascape has some unique design advantages, a close examination should also provide potential tool users with more insight into the kinds of services and features agent modeling toolkits provide in general.

Wolfgang Balzer, Karl R. Brendel and Solveig Hofmann
Journal of Artificial Societies and Social Simulation 4 (2) 1

Kyeywords: Social Simulation, Game Theory, Discrete Event Simulation, Model Theory, Confirmation, Impossibility Theorem
Abstract: The aim of this note is to clarify and to correct some arguments which are used in the debate about the comparison of discrete social simulation with other methodologies used in the study of social phenomena, notably those of game theory. Though part of what will be said also applies to non-discrete simulation, the arguments are investigated only as far as the discrete case is concerned. The main claims against each of both scientific approaches are considered in particular, i.e. "impossibility" of game theory and "unsoundness" of simulation studies. Regarding the latter, arguments are presented that items occurring in simulation studies correspond to the formal constituents of a scientific theory, and thus a comparison of both approaches on the same level is justified. The question whether a superiority of one of the two approaches can be stated is illuminated in the light of four dimensions: empirical adequacy, theoretical fruitfulness, social relevance, and simplicity. This leads to the conclusion that both claims are unjustified and should be avoided in the debate about the role and merits of social simulation.

Scott Moss
Journal of Artificial Societies and Social Simulation 4 (2) 2

Kyeywords: Game Theory, Agent, Multi Agent System, Simulation, Market, Intermediation
Abstract: The purpose of this paper is to describe current practice in the game theory literature, to identify particular characteristics that ensure the literature is remote from anything we observe and to demonstrate an alternative drawn from agent based social simulation. The key issue is the process of social interaction among agents. A survey of game theoretic models found no models representing interaction among more than three agents, though sometimes more agents were involved in a round robin tournament. An ABSS model is reported in which there is a dense pattern of interaction among agents and outputs from the model are shown to have the same statistical signature as high-frequency data from competitive retail and financial markets. Moreover, the density of agent interaction is seen to be necessary both to obtain the validating statistical signature and for simulated market efficiency. As far as competitive markets are concerned, game theoretic models evidently assume away the source of the properties observed in real high frequency data and also the properties required for market efficiency.

Kai-H. Brassel
Journal of Artificial Societies and Social Simulation 4 (3) 10

Kyeywords: Object-Oriented Simulation, Multi-Paradigm Modelling, Java, Simulation Framework, Web-Based Simulation, Simulation Visualization
Abstract: Social science research calls for the explorative modelling of complex problem domains. A modelling tool that aims at supporting this kind of effort has to strike the balance between offering sufficient flexibility for free exploration on the one hand and effective measures to relieve the modeler from the more cumbersome parts of programming on the other. The Java-based VSEit framework, presented in this paper, embodies a pragmatic approach to strike that middle ground. One key element of the VSEit architecture is the supplementation of the usual object-oriented class concept with the capability for specifying types of model entities and structures at a high semantic level.

Yvonne Haffner and Stefan Gramel
Journal of Artificial Societies and Social Simulation 4 (3) 11

Kyeywords: Nitrate, Water Supply, Object-Oriented Simulation, Environmental Sustainability
Abstract: The computer based model presented in this paper regards strategies for water supply companies to deal with nitrate pollution of groundwater aquifers. In Germany, as well as in many other European regions, nitrate pollution is one of the most important problems for water protection and water supply. The simulation of an existing water supply company shows a high level of conformance between simulation results and economic data of the company. The simulation of scenarios with high nitrate pollution shows important differences between the strategies of using deeper aquifers, of technical treatment of raw water, and of co-operation with the agriculture regarding costs and environmental sustainability. Also these results reflect fairly well the situation in Germany.

Wolfgang Kerber and Nicole J. Saam
Journal of Artificial Societies and Social Simulation 4 (3) 2

Kyeywords: Competition, Hayek, Knowledge, Innovation, Merger Control, Concentration, Simulation, Lock-In, Evolutionary Economics
Abstract: Hayek's well-known evolutionary concept of "competition as a discovery procedure" can be characterized as a parallel process of experimentation, in which rivalrous firms generate and test hypotheses about the best way to fulfill the consumers' preferences. Through this permanent process of variation and selection of hypotheses (innovation / imitation) a process of knowledge accumulation can take place. The central aim of our paper is to model the basic Hayekian learning mechanism, which consists of experimentation and mutual learning, and to ask for determinants of the rapidity of knowledge accumulation. In our multilevel simulation model, on the micro level, firms create new hypotheses through mutation. On the macro level, on the market, these hypotheses meet and the best firm is determined. All firms then imitate the best firm. In our model, 100 of these periods which consist of an innovation and an imitation phase are simulated. We presume that decentrality is crucial for the working of the knowledge-generating process, because a larger number of independently innovating firms leads to more experimentation. We investigate into the impact of firm concentration, the impact of the decentralization of firms, as well as the impact of impediments in imitation like lock-ins on the growth rate of knowledge accumulation. Our simulation results show that the number of firms is positively correlated with the rapidity of knowledge accumulation suggesting a new argument for a critical assessment of mergers in competition policy.

Thomas Brenner
Journal of Artificial Societies and Social Simulation 4 (3) 4

Kyeywords: Industrial Clusters, Simulations, Evolution, Spatial Agglomeration
Abstract: Localised industrial clusters have received much attention in economic research in the last decade. They are seen as one of the reasons for the economic success of certain regions in comparison to others. This paper studies the evolution of such industrial clusters. To this end, a spatial structure of regions is set up and the entry, exit, and growth of firms within these regions is modelled and studied with the help of simulations. Several mechanisms that are often stated to be important in the context of localised industrial clusters are explicitly modelled. The influence of these mechanisms on the geographical concentration of industries is studied.

Nigel Gilbert, Andreas Pyka and Petra Ahrweiler
Journal of Artificial Societies and Social Simulation 4 (3) 8

Kyeywords: Innovation, Simulation of Social Networks, Mobile Communications, Biotechnology, Kene
Abstract: A multi-agent simulation embodying a theory of innovation networks has been built and used to suggest a number of policy-relevant conclusions. The simulation animates a model of innovation (the successful exploitation of new ideas) and this model is briefly described. Agents in the model representing firms, policy actors, research labs, etc. each have a knowledge base that they use to generate \'artefacts\' that they hope will be innovations. The success of the artefacts is judged by an oracle that evaluates each artefact using a criterion that is not available to the agents. Agents are able to follow strategies to improve their artefacts either on their own (through incremental improvement or by radical changes), or by seeking partners to contribute additional knowledge. It is shown though experiments with the model's parameters that it is possible to reproduce qualitatively the characteristics of innovation networks in two sectors: personal and mobile communications and biotechnology.

Marie-Edith Bissey and Guido Ortona
Journal of Artificial Societies and Social Simulation 5 (2) 2

Kyeywords: Cooperation, Conventions, Prisoner's Dilemma, Social Simulation, SWARM
Abstract: This paper describes a study of the robustness of cooperative conventions. We observe the effect of the invasion of non-cooperating subjects into a community adopting a cooperative convention. The convention is described by an indefinitely repeated prisoner-dilemma game. We check the effects on the robustness of the cooperating convention of two characteristics of the game, namely the size of the prisonner-dilemma groups and the "intelligence" of the players. The relevance for real-world problems is considered. We find that the "intelligence" of the players plays a crucial role in the way players learn to cooperate. The simulation program is written in SWARM (Java version).

Thomas Sauerbier
Journal of Artificial Societies and Social Simulation 5 (2) 5

Kyeywords: Microsimulation, Monte Carlo Simulation, Micro Data, Simulation Languages, Simulation Systems, UMDBS, MISTRAL
Abstract: Microsimulation is a powerful method for analysis and forecasting especially in the field of economics and social science. One of the main reasons for its relatively rare usage is that until now there has been no standard software available. The Universal Micro DataBase System, UMDBS, is a new tool that runs on any Windows PC. It is suited for all tasks involved in running a microsimulation starting from the import of external data, the development of the simulation model, to the analysis of the results. It includes MISTRAL, an integrated modelling language that allows implementing the simulation models as well as analysing the micro data. After a short introduction to microsimulation, this article first presents the UMDBS and its main functions. Then an overview to the new modelling language MISTRAL is given including the features, the structure, and the implementation. Finally information is given about how to get UMDBS for free.

David Brichoux and Paul E. Johnson
Journal of Artificial Societies and Social Simulation 5 (3) 1

Kyeywords: Protest; Social Movements; Swarm; Simulation; Critical Mass
Abstract: This paper presents an agent-based simulation model of protest activity. Agents are located in a two dimensional grid and have limited ability to observe the behavior of other agents in the grid. The model is used to explore questions inspired by research on different theories of individual motivation and the so-called theory of critical mass. The simulations describe individuals who support an effort to change a policy, but acting in support of that effort is costly. When the marginal effect of participation reaches a certain level, people are more likely to get involved. With certain configurations of parameter values, the simulations produce no sustained widespread participation in protest regardless of the presence of activists; under other conditions high levels of protest are usually sustained, even without activists. However, the addition of a surprisingly small group of activists radically changes the aggregate behavior of the model under some conditions, making high and sustained protest possible when it otherwise would not have been.

Ian Lustick
Journal of Artificial Societies and Social Simulation 5 (3) 7

Kyeywords: Simulation platform, Political identity, Constructivist identity theory
Abstract: PS-I (Political Science-Identity) is an agent-based computer simulation platform originally developed to operationalize, refine, and test competing versions of constructivist identity theory. Based on an earlier prototype, the ABIR (Agent-Based Identity Repertoire) model, agents with repertoires of identities (or other potentialities) interact in localities of specifiable size and are influenced as well by cross-landscape values attached to particular identities. These values change over time, thereby simulating conditions in which individuals may express latent identities, or learn to use new identities, because of local pressures toward conformity and/or overall shifts in the relative attractiveness of presenting oneself as attached to one identity or another. Large batches of controlled virtual histories are used for comparative and statistical analysis. PS-I has been designed with two imperatives in mind: ease of deployment by users who know nothing of computer programming; and systematic correspondence between the algorithms for agent behavior and corroborated theoretical positions in political science and psychology. The non-technical user—the user with no programming skillsc—can PS-I, to build and execute sophisticated models of substantial academic and policy interest. PS-I thus differs very significantly from existing platforms complexions and governance patterns are now under development. The substantive problems of interest that triggered the development of ABIR and PS-I related to the crisis facing social scientists using constructivist theories of identity to understand patterns of mobilization, attachment, and conflict based on cultural, ethnic, religious, or other traits. Athough constructivist theory has been very successful in demonstrating the ineffectiveness of older “primordial” or “essentialist” notions of political identity, and in showing that identities are, within limits, fluid, tradeable, manipulable, and multiple, scholars employing these theories have been much less successful in studying the conditions under which and the limits within which collective identities can be stabilized, destabilized, created, or destroyed. The paper illustrates use of PS-I to study the dynamics of identity politics in a “typical” authoritarian Muslim Middle Eastern country subjected to globalizing pressures, religious mobilization, and conflict in culturally divided societies.

John Scott and Scott Moss
Journal of Artificial Societies and Social Simulation 5 (3) 9

Kyeywords: European Social Simulation Association, development of social simulation research, education and application.
Abstract: There is growing agreement that the time has come to form a learned society to promote the development of social simulation. The undersigned wish to propose the formation of a European Social Simulation Association (ESSA). Recognising parallel interests and developments in North America, Latin America and Australasia, we would intend ESSA to coordinate with similar organisations in those and other regions to organise an international federation to support the development of social simulation research, education and application.

Franziska Klügl and Ana L. C. Bazzan
Journal of Artificial Societies and Social Simulation 7 (1) 1

Kyeywords: Self-Organising System, Adaptation and Learning, Game-Theoretic Approaches, Traffic Simulation
Abstract: One challenge to researchers dealing with traffic management is to find efficient ways to model and predict traffic flow. Due to the social nature of traffic, most of the decisions are not independent. Thus, in traffic systems the inter-dependence of actions leads to a high frequency of implicit co-ordination decisions. Although there are already systems designed to assist drivers in these tasks (broadcast, Internet, etc.), such systems do not consider or even have a model of the way drivers decide. Our research goal is the study of commuting scenarios, drivers' decision-making, its influence on the system as a whole, and how simulation can be used to understand complex traffic systems. The present paper addresses two key issues: simulation of driver decision-making, and the role of a traffic forecast component. The former is realised by a naïve model for the route choice adaptation, where commuters behaviour is based on heuristics they evolve. The second issue is realised via a traffic control system which perceives drivers' decisions and returns a forecast, thus allowing drivers to decide the actual route selection. For validation, we use empirical data from real experiments and show that the heuristics drivers evolve lead to a situation similar to that obtained in the real experiments. As for the forecast scenario, our results confirm that a traffic system in which a large share of drivers reacts to the forecast will not develop into equilibrium. However, a more stable situation arises by introducing some individual tolerance to sub-optimal forecasts.

Claudia Pahl-Wostl and Eva Ebenhöh
Journal of Artificial Societies and Social Simulation 7 (1) 3

Kyeywords: Social Simulation, Experimental Economics, Common Pool Resource Games, Adaptive Toolbox, Altruistic Punishment
Abstract: This article describes a social simulation model based on an economic experiment about altruistic behavior. The experiment by Fehr and Gächter showed that participants made frequent use of costly punishment in order to ensure continuing cooperation in a common pool resource game. The model reproduces not only the aggregated but also the individual data from the experiment. It was based on the data rather than theory. By this approach new insights about human behaviour and decision making may be found. The model was not designed as a stand-alone model, but as a starting point for a comprehensive Adaptive Toolbox Model. This may form a framework for modelling results from different economic experiments, comparing results and underlying assumptions, and exploring whether the insights thus gained also apply to more realistic situations.

Robert Tobias and Carole Hofmann
Journal of Artificial Societies and Social Simulation 7 (1) 6

Kyeywords: Evaluation, Simulation Framework, Agent Based Modeling, Java, Theory Based Modeling, Data Based Modeling, Social Intervention Planning
Abstract: This paper compares four freely available programming libraries for support of social scientific agent based computer simulation: RePast, Swarm, Quicksilver, and VSEit. Our aim is evaluation to determine the simulation framework that is the best suited for theory and data based modeling of social interventions, such as information campaigns. Our first step consisted in an Internet search for programming libraries and the selection of suitable candidates for detailed evaluation on the basis of 'knock out' criteria. Next, we developed a rating system and assessed the selected simulation environments on the basis of the rating criteria. The evaluation was based on official program documentation, statements by developers and users, and the experiences and impressions of the evaluators. The evaluation results showed the RePast environment to be the clear winner. In a further step, the evaluation results were weighted according to effort/time/energy saved by social scientists by using the particular ready-made programming library as compared to doing their own programming. Once again, the weighted results show RePast to win out over the other Java based programming libraries examined.

Catherine Dibble and Philip G. Feldman
Journal of Artificial Societies and Social Simulation 7 (1) 7

Kyeywords: Simulation tools, Geographic Simulation, Network Landscapes, Epidemic Control, 3D Landscapes, GeoComputation, Small-world
Abstract: Our GeoGraph 3D extensions to the RePast agent-based simulation platform support models in which mobile agents travel and interact on rugged terrain or on network landscapes such as social networks of established organizational teams or spatial networks at any scale from rooms within buildings to urban neighborhoods to large geographic networks of cities. Interactive GeoGraph 3D visualizations allow researchers to zoom and pan within the simulation landscape as the model runs. Model-specific 3D representations of agents flock together on terrain landscapes, and teleport or travel along links on network landscapes. Agents may be displayed on network nodes either as individual agents or as dynamic 3D bar charts that reflect the composition of each node's population. Batch modes support scientific control via fully separated random number series, customized parameter combinations, and automatic data collection for many thousands of simulation runs. This paper introduces the GeoGraph 3D computational laboratory and briefly describes three representative GeoGraph models along with basic GeoGraph 3D capabilities and components.

Stanislaw Raczynski
Journal of Artificial Societies and Social Simulation 7 (2) 8

Kyeywords: Simulation, Modeling, Terrorism, Discrete Event, Agent-Oriented, Social Simulation, Soft Systems
Abstract: A discrete-event model of the dynamics of certain social structures is presented. The structures include terrorist organizations, anti-terrorism and terrorism-supporting structures. The simulation shows the process of creating the structures and their interactions. As a result, we can see how the structure size changes and how the interactions work, and the process of destroying terrorist organization links by the anti-terrorist agents. The simulation is agent-oriented and uses the PASION simulation system.

Bruce Edmonds and David Hales
Journal of Artificial Societies and Social Simulation 7 (2) 9

Kyeywords: Negotiation, Haggling, Bargaining, Simulation, Dialogue, Beliefs, Causation, Representation, Numbers, Mental Models, Search, Participatory Methods
Abstract: We present a computational simulation which captures aspects of negotiation as the interaction of agents searching for an agreement over their own mental model. Specifically this simulation relates the beliefs of each agent about the action of cause and effect to the resulting negotiation dialogue. The model highlights the difference between negotiating to find any solution and negotiating to obtain the best solution from the point of view of each agent. The later case corresponds most closely to what is commonly called "haggling". This approach also highlights the importance of what each agent thinks is possible in terms of actions causing changes and in what the other agents are able to do in any situation to the course and outcome of a negotiation. This simulation greatly extends other simulations of bargaining which usually only focus on the case of haggling over a limited number of numerical indexes. Three detailed examples are considered. The simulation framework is relatively well suited for participatory methods of elicitation since the "nodes and arrows" representation of beliefs is commonly used and thus accessible to stakeholders and domain experts.

Luis R. Izquierdo, Nicholas M. Gotts and J. Gareth Polhill
Journal of Artificial Societies and Social Simulation 7 (3) 1

Kyeywords: Social Dilemmas, Case-Based Reasoning, Prisoner's Dilemma, Agent-Based Simulation, Analogy, Game Theory, Aspiration Thresholds, Equilibrium
Abstract: In this paper social dilemmas are modelled as n-player games. Orthodox game theorists have been able to provide several concepts that narrow the set of expected outcomes in these models. However, in their search for a reduced set of solutions, they had to pay a very high price: they had to make disturbing assumptions such as instrumental rationality or common knowledge of rationality, which are rarely observed in any real-world situation. We propose a complementary approach, assuming that people adapt their behaviour according to their experience and look for outcomes that have proved to be satisfactory in the past. These ideas are investigated by conducting several experiments with an agent-based simulation model in which agents use a simple form of case-based reasoning. It is shown that cooperation can emerge from the interaction of selfish case-based reasoners. In determining how often cooperation occurs, aspiration thresholds, the agents' representation of the world, and their memory all play an important and interdependent role. It is also argued that case-based reasoners with high enough aspiration thresholds are not systemically exploitable, and that if agents were sophisticated enough to infer that other players are not exploitable either, they would eventually cooperate.

Marie-Edith Bissey, Mauro Carini and Guido Ortona
Journal of Artificial Societies and Social Simulation 7 (3) 3

Kyeywords: Electoral Systems, Electoral Simulation, Representativeness, Governability
Abstract: he paper describes a program for comparing electoral systems based on the simulation of the preferences of the voters. The parameters requested (distribution of first preferences, district magnitude, etc) are set up by the user. The program produces the resulting Parliament under a number of electoral systems, an index of representativeness and an index of governability. The first part of the paper describes the characteristics of the program. In the second part it is used to compare eleven electoral systems in two virtual but realistic cases.

Benjamin M. Eidelson and Ian Lustick
Journal of Artificial Societies and Social Simulation 7 (3) 6

Kyeywords: Smallpox, Bioterrorism, Agent-Based Modeling, Stochastic Simulation, Vaccination Policy
Abstract: Because conjectural 'thought experiments' can be formalized, refined, and conducted systematically using computers, computational modeling is called for in situations that demand robust quantitative study of phenomena which occur only rarely, or may never occur at all. In light of mounting concerns regarding the threats of bioterrorism in general and smallpox in specific, we developed a stochastic agent-based model, VIR-POX, in order to explore the viability of available containment measures as defenses against the spread of this infectious disease. We found the various vaccination and containment programs to be highly interdependent, and ascertained that these policy options vary not only in their mean effects, but also in their subordination to factors of chance or otherwise uncontrollable interference, relationships which themselves fluctuate across ranges of the counterfactual distribution. Broadly speaking, ring vaccination rivaled mass vaccination if a very substantial proportion of smallpox cases could be detected and isolated almost immediately after infection, or if residual herd immunity in the population was relatively high. Pre-attack mass vaccination and post-attack mass vaccination were equivalent in their capacities to eliminate the virus from the population within five months, but the pre-attack strategy did so with significantly fewer deaths in the process. Our results suggest that the debate between ring and mass vaccination approaches may hinge on better understanding residual herd immunity and the feasibility of early detection measures.

Ana Maria Ramanath and Nigel Gilbert
Journal of Artificial Societies and Social Simulation 7 (4) 1

Kyeywords: Participatory Simulation, Software Methodologies, Development Techniques
Abstract: It is becoming widely accepted that applied social simulation research is more effective if potential users and stakeholders are closely involved in model specification, design, testing and use, using the principles of participatory research. In this paper, a review of software engineering principles and accounts of the development of simulation models are used as the basis for recommendations about some useful techniques that can aid in the development of agent-based social simulation models in conjunction with users. The authors' experience with scenario analysis, joint analysis of design workshops, prototyping and user panels in a collaborative participatory project is described and, in combination with reviews from other participatory projects, is used to suggest how these techniques might be used in simulation-based research.

Wendelin Reich
Journal of Artificial Societies and Social Simulation 7 (4) 4

Kyeywords: Formal Logic, Social Interaction, Social Simulation, Agents, Social Meta-Reasoning, Reasoning About Reasoning
Abstract: Formal logic has become an invaluable tool for research on multi-agent systems, but it plays a minor role in the more applied field of agent-based social simulation (ABSS). We argue that logical languages are particularly useful for representing social meta-reasoning, that is, agents' reasoning about the reasoning of other agents. After arguing that social meta-reasoning is a frequent and important social phenomenon, we present a set of general criteria (functional completeness, understandability, changeability, and implementability/executability) to compare logic to two alternative formal methods: black box techniques (e.g., neural networks) and decision-theoretical models (e.g., game theory). We then argue that in terms of functional completeness, understandability and changeability, logical representations of social meta-reasoning compare favorably to these two alternatives.

Oswaldo Terán
Journal of Artificial Societies and Social Simulation 7 (4) 5

Kyeywords: Methodology, Modelling, Social Simulation, MABS, Theory, Philosophy
Abstract: This paper suggests procedures for decreasing misunderstanding between modellers in social simulation, aiming at helping modellers comprehending a certain phenomena from different perspectives, being aware of the relativity of each approach, and drawing conclusions from the different perspectives. A hierarchy of four levels of language, namely, cultural or natural language, modelling and theoretical paradigm, modelling language, and simulation programming language, is proposed and exemplified as a framework for examining simulation models - assumptions of language embedded in the model at each level are made explicit. Afterwards, switching between languages is suggested for achieving different interpretations and alternative explanations of a model; alongside, as a synthesis from different interpretations, to draw in an interpretive conclusion is suggested. In addition, Interpretive Systemology, a soft systems approach, is proposed as another innovative alternative for better understanding social simulation models, as it recommends undertaking the whole modelling process from different perspectives. The hierarchy of languages, and switching between languages, will be placed against the whole modelling process as understood by Edmonds (2000).

Johannes Kottonau and Claudia Pahl-Wostl
Journal of Artificial Societies and Social Simulation 7 (4) 6

Kyeywords: Attitude Formation, Social Simulation, Voting Behavior
Abstract: Understanding the dynamics of attitude formation is a key issue in social psychology. The paper presents a computational model for simulating the formation and change of attitudes and the influence of the strength of attitudes on behavior. The main conceptual challenge was to capture not only the traditional attitude concept but the full concept of attitude strength. This required combining different theoretical approaches within an integrated modeling framework. The dynamics of political attitudes of German citizens were chosen as specific application area because of the considerable amount of empirical data available. The model was tested by simulating the effects of different voting campaign strategies on the outcome of an election. Uncertainties in model parameters were accounted for by using Monte Carlo simulations. The implications of specific theoretical assumptions were investigated by performing model simulations for different model structures. The paper shows the potential of social simulation when it comes to bringing together different theoretical approaches. The integration within a model exposes gaps and inconsistencies and allows formulating hypotheses for further empirical investigations. The model has a modular structure and provides a rich repository for other modelers who are working in the field of attitude simulation.  

Deborah Duong and John Grefenstette
Journal of Artificial Societies and Social Simulation 8 (1) 1

Kyeywords: Agent-Based Model, Computational Social Theory, Economics Simulation, Symbolic Interactionism, Emergent Language, Sociological Roles
Abstract: SISTER, a Symbolic Interactionist Simulation of Trade and Emergent Roles, captures a fundamental social process by which macro level roles emerge from micro level symbolic interaction. The knowledge in a SISTER society is held culturally, suspended in the mutual expectations agents have of each other based on signs (tags) that they read and display. In this study, this knowledge includes how to create composite goods. The knowledge of coordinating their creation arises endogenously. A symbol system emerges to denote these tasks. In terms of information theory, the degree of mutual information between the agent\'s signs (tags) and their behavior increases over time. The SISTER society of this study is an economic simulation, in which agents have the choice of growing all the goods they need by themselves, or concentrating their efforts in making more of fewer goods and trading them for other goods. They induce the sign of an agent to trade with, while at the same time, they induce a sign to display. The signs come to mean sets of behaviors, or roles, through this double induction. A system of roles emerges, holding the knowledge of social coordination needed to distribute tasks among the agents.

Pieter Buzing, A.E. Eiben and Martijn C. Schut
Journal of Artificial Societies and Social Simulation 8 (1) 2

Kyeywords: Social Simulation, Communication, Cooperation, Artificial Societies
Abstract: The main contribution of this paper is threefold. First, it presents a new software system for empirical investigations of evolving agent societies in SugarScape like environments. Second, it introduces a conceptual framework for modeling cooperation in an artificial society. In this framework the environmental pressure to cooperate is controllable by a single parameter, thus allowing systematic investigations of system behavior under varying circumstances. Third, it reports upon results from experiments that implemented and tested environments based upon this new model of cooperation. The results show that the pressure to cooperate leads to the evolution of communication skills facilitating cooperation. Furthermore, higher levels of cooperation pressure lead to the emergence of increased communication.

J. Gareth Polhill, Luis R. Izquierdo and Nicholas M. Gotts
Journal of Artificial Societies and Social Simulation 8 (1) 5

Kyeywords: Agent Based Modelling, Floating Point Arithmetic, Interval Arithmetic, Replication
Abstract: This paper will explore the effects of errors in floating point arithmetic in two published agent-based models: the first a model of land use change (Polhill et al. 2001; Gotts et al. 2003), the second a model of the stock market (LeBaron et al. 1999). The first example demonstrates how branching statements with floating point operands of comparison operators create a high degree of nonlinearity, leading in this case to the creation of 'ghost' agents -- visible to some parts of the program but not to others. A potential solution to this problem is proposed. The second example shows how mathematical descriptions of models in the literature are insufficient to enable exact replication of work since mathematically equivalent implementations in terms of real number arithmetic are not equivalent in terms of floating point arithmetic.

Bin Hu and Xia Gongcheng
Journal of Artificial Societies and Social Simulation 8 (2) 1

Kyeywords: Group Behaviour, Qualitative Simulation, QSIM, Causal Graph, Group Dynamics
Abstract: This paper presents a qualitative simulation method for analyzing employee group behavior by integrating QSIM (Qualitative SIMulation) with basic causal reasoning. A description method for complex interactions between environment, management policy and group behaviour is designed. A qualitative simulation method including the simulation rules and a simulation engine is then proposed. The validation of the proposed method is tested, and an example is given of how this method can be applied to the development of management policy for the effective motivation of employees. Simulation results show that this method can be used to explain and predict changes in group behavior, and also to aid in decision making on employee group management.

Boris Galitsky and Mark Levene
Journal of Artificial Societies and Social Simulation 8 (2) 6

Kyeywords: Simulation of Competition, Subscribing to Rating, Web Portals
Abstract: We simulate the process of possible interactions between a set of competitive services and a set of portals that provide online rating for these services. We argue that to have a profitable business, these portals are forced to have subscribed services that are rated by the portals. To satisfy the subscribing services, we make the assumption that the portals improve the rating of a given service by one unit per transaction that involves payment. In this study we follow the \'what-if\' methodology, analysing strategies that a service may choose from to select the best portal for it to subscribe to, and strategies for a portal to accept the subscription such that its reputation loss, in terms of the integrity of its ratings, is minimised. We observe that the behaviour of the simulated agents in accordance to our model is quite natural from the real-would perspective. One conclusion from the simulations is that under reasonable conditions, if most of the services and rating portals in a given industry do not accept a subscription policy similar to the one indicated above, they will lose, respectively, their ratings and reputations, and, moreover the rating portals will have problems in making a profit. Our prediction is that the modern portal-rating based economy sector will eventually evolve into a subscription process similar to the one we suggest in this study, as an alternative to a business model based purely on advertising.

Shah Jamal Alam, Frank Hillebrandt and Michael Schillo
Journal of Artificial Societies and Social Simulation 8 (3) 5

Kyeywords: Gift Exchange, Multiagent Systems, Habitus-Field Theory, Social Simulation
Abstract: In this paper, the implications of applying the idea of gift exchange mechanism, inspired from Pierre Bourdieu's sociological theories, into a market-based multiagent system are explored. Our work is directed in the continuation of investigations by Knabe (2002), who addressed the formation of different organizations structures between providers in a profit-oriented market. We nevertheless scrutinize various hypotheses centered to gift exchange in which an agent sacrifices its profit for a long-term binding relationship. The idea is to aim a larger profit through alliances that are formed as an effect of gift exchange. Our suggestion is that a multiagent system (MAS) based on the social mechanism of gift exchange performs a high level of robustness and durability. The market in our case comprises of customers and providers agents. The former calls for proposals for the tasks they introduce in the market, while the latter proceed with the execution of tasks based on their abilities and other circumstances. In well defined cases, the providers are able to delegate tasks to other providers. This allows them to give presents to other providers so that the gift exchange mechanism becomes possible. The agents are either profit-oriented or the ones who prefer exchanging gifts and are in pursuit of others who also practice this mechanism. A number of interesting scenarios are examined that include preservation of a hierarchical structure in the market, situations resulting in the forming of an alliance between two providers, and split of profit-oriented and gift-giving agents.

Joerg Becker, Bjoern Niehaves and Karsten Klose
Journal of Artificial Societies and Social Simulation 8 (4) 1

Kyeywords: Simulation, Epistemology, Reference Framework, Ontology, Consensus-Oriented Approach
Abstract: Simulation is a widely-used research method going back to a long history in numerous disciplines and in many research communities. But the epistemological status of simulation remains unclear and very much depends on the individual propositions of the researcher. At this juncture, we develop a reference framework which allows structuring and systematizing (often hidden) epistemological assumptions made by researchers when applying simulation as a research method. Afterwards, we show how to apply the reference framework by analysing the influence of the consensus-oriented approach (as one possible epistemological position) on simulation research.

Scott Moss and Bruce Edmonds
Journal of Artificial Societies and Social Simulation 8 (4) 13

Kyeywords: Methodology, Agent Based Social Simulation, Qualitative Analysis; Evidence; Conditions of Application; History of Science
Abstract: The paper investigates what is meant by "good science" and "bad science" and how these differ as between the natural (physical and biological) sciences on the one hand and social sciences on the other. We conclude on the basis of historical evidence that the natural science are much more heavily constrained by evidence and observation than by theory while the social sciences are constrained by prior theory and hardly at all by direct evidence. Current examples of the latter proposition are taken from recent issues of leading social science journals. We argue that agent based social simulations can be used as a tool to constrain the development of a new social science by direct (what economists dismiss as anecdotal) evidence and that to do so would make social science relevant to the understanding and influencing of social processes. We argue that such a development is both possible and desirable. We do not argue that it is likely.

Petra Ahrweiler and Nigel Gilbert
Journal of Artificial Societies and Social Simulation 8 (4) 14

Kyeywords: Evaluation, Social Simulation, Standard View, Constructivist View, User Community
Abstract: This contribution deals with the assessment of the quality of a simulation by discussing and comparing "real-world" and scientific social simulations. We use the example of the Caffè Nero in Guildford as a 'real-world' simulation of a Venetian café. The construction of everyday simulations like Caffè Nero has some resemblance to the construction procedure of scientific social simulations. In both cases, we build models from a target by reducing the characteristics of the latter sufficiently for the purpose at hand; in each case, we want something from the model we cannot achieve easily from the target. After briefly discussing the 'ordinary' method of evaluating simulations called the 'standard view' and its adversary, a constructivist approach asserting that 'anything goes', we heed these similarities in the construction process and apply evaluation methods typically used for everyday simulations to scientific simulation and vice versa. The discussion shows that a 'user community view' creates the foundation for every evaluation approach: when evaluating the Caffè Nero simulation, we refer to the expert community (customers, owners) who use the simulation to get from it what they would expect to get from the target; similarly, for science, the foundation of every validity discussion is the ordinary everyday interaction that creates an area of shared meanings and expectations. Therefore, the evaluation of a simulation is guided by the expectations, anticipations and experience of the community that uses it – for practical purposes (Caffè Nero), or for intellectual understanding and for building new knowledge (science simulation).

Nuno David, Jaime Simão Sichman and Helder Coelho
Journal of Artificial Societies and Social Simulation 8 (4) 2

Kyeywords: Computer and Social Sciences, Agent-Based Simulation, Intentional Computation, Program Verification, Intentional Verification, Scientific Knowledge
Abstract: The classical theory of computation does not represent an adequate model of reality for simulation in the social sciences. The aim of this paper is to construct a methodological perspective that is able to conciliate the formal and empirical logic of program verification in computer science, with the interpretative and multiparadigmatic logic of the social sciences. We attempt to evaluate whether social simulation implies an additional perspective about the way one can understand the concepts of program and computation. We demonstrate that the logic of social simulation implies at least two distinct types of program verifications that reflect an epistemological distinction in the kind of knowledge one can have about programs. Computer programs seem to possess a causal capability (Fetzer, 1999) and an intentional capability that scientific theories seem not to possess. This distinction is associated with two types of program verification, which we call empirical and intentional verification. We demonstrate, by this means, that computational phenomena are also intentional phenomena, and that such is particularly manifest in agent-based social simulation. Ascertaining the credibility of results in social simulation requires a focus on the identification of a new category of knowledge we can have about computer programs. This knowledge should be considered an outcome of an experimental exercise, albeit not empirical, acquired within a context of limited consensus. The perspective of intentional computation seems to be the only one possible to reflect the multiparadigmatic character of social science in terms of agent-based computational social science. We contribute, additionally, to the clarification of several questions that are found in the methodological perspectives of the discipline, such as the computational nature, the logic of program scalability, and the multiparadigmatic character of agent-based simulation in the social sciences.

Günter Küppers and Johannes Lenhard
Journal of Artificial Societies and Social Simulation 8 (4) 3

Kyeywords: Generative Mechanism, Imitation, Patterns, Simulation, Validation
Abstract: In most cases, the meaning of computer simulation is strongly connected to the idea numerical calculations. A computer simulation is a numerical solution of a complex mathematical problem. Therefore, the problem of validation of its results should be only a problem of judging the underlying computational methods. However, it will be argued, that this is not the case. It is consensus in literature that validation constitutes one of the central epistemological problems of computer simulation methods. Especially in the case of simulations in the social sciences the answers given by many authors are not satisfactory. The following paper attempts to show how the characteristics of simulation, i.e. the imitation of a dynamic, constitute the problem of validation even in the case of the natural sciences and what consequences arise. Differences as well as common grounds between social and natural sciences will be discussed.

Bernd-O. Heine, Matthias Meyer and Oliver Strangfeld
Journal of Artificial Societies and Social Simulation 8 (4) 4

Kyeywords: Computer Simulation, Stylised Facts, Methodology, Groves Mechanism, Collusion, Game Theory
Abstract: The application of computer simulation as a research method raises two important questions: (1) Does simulation really offer added value over established methods? (2) How can the danger of arbitrariness caused by the extended modelling possibilities be minimised? We present the concept of stylised facts as a methodological basis for approaching these questions systematically. In particular, stylised facts provide a point of reference for a comparative analysis of models intended to explain an observable phenomenon. This is shown with reference to a recent discussion in the "economic analysis of accounting" literature where established methods, i.e. game theory, as well as computer simulations are used: the susceptibility of the "Groves mechanism" to collusion. Initially, we identify six stylised facts on the stability of collusion in empirical studies. These facts serve as a basis for the subsequent comparison of four theoretical models with reference to the above questions: (1) We find that the simulation models of Krapp and Deliano offer added value in comparison to the game theoretical models. They can be related to more stylised facts, achieve a better reproduction and exhibit far greater potential for incorporating yet unaddressed stylised facts. (2) Considered in the light of the stylised facts to which the models can be related, Deliano's simulation model exhibits considerable arbitrariness in model design and lacks information on its robustness. In contrast, Krapp demonstrates that this problem is not inherent to the method. His simulation model methodically extends its game theoretical predecessors, leaving little room for arbitrary model design or questionable parameter calibration. All in all, the stylisedfactsconcept proved to be very useful in dealing with the questions simulation researchers are confronted with. Moreover, a "research landscape" emerges from the derived stylised facts pinpointing issues yet to be addressed.

Alex Schmid
Journal of Artificial Societies and Social Simulation 8 (4) 5

Kyeywords: Epistemology, Simulation, Truth Theories, Validation
Abstract: To understand the epistemological meaning of simulation, it does not suffice to interpret simulation practice and theory in the framework of philosophy of science alone. Theory, experiment, measurement and observation are important activities of the scientific method. But what regards an epistemological interpretation of simulation, philosophical truth theories allow gaining additional insights. This paper discusses philosophical truth theories – e.g. the correspondence, coherence and consensus theory – and relates them to simulation practice and methodology, focussing on validation.

Ulrich Frank and Klaus G. Troitzsch
Journal of Artificial Societies and Social Simulation 8 (4) 7

Kyeywords: Simulation, Epistemology, Methodology
Abstract: This special section includes papers originally presented at a workshop on \'Epistemological Perspectives on Simulation\' in July 2004 at the University of Koblenz, in which some thirty colleagues participated. It had been our impression that there was (and still is) a small, but growing number of researchers who are interested in investigating the preconditions of successfully deploying simulation as a research tool. We were convinced that discussing the epistemological status of simulation in a cross-disciplinary setting could contribute to a deeper understanding of relevant issues and so it proved.

Chung-Yuan Huang, Chuen-Tsai Sun and Hsun-Cheng Lin
Journal of Artificial Societies and Social Simulation 8 (4) 8

Kyeywords: Small-World Network Model, Contagion Problem, Local Information, Epidemic Simulation
Abstract: As part of Watts and Strogatz\'s small-world model of complex networks, local information mechanisms such as landscape properties are used to approximate real-world conditions in social simulations. The authors investigated the influence of local information on social simulations based on the small-world network model, using a cellular automata variation with added shortcuts as a test platform for simulating the spread of an epidemic disease or cultural values/ideas. Results from experimental simulations show that the percentage of weak individuals should be considered significant local information, but vertex degree influences and the distribution patterns of weak individuals should not. When exploring contagion problems, the results encourage a future emphasis on setting and the proportions of specific values of local information related to infection strength or resistance, and a reduced emphasis on the detailed topological structure of small-world network models and the distribution patterns of specific values of local information.

Guillaume Deffuant, Scott Moss and Wander Jager
Journal of Artificial Societies and Social Simulation 9 (1) 1

Kyeywords: Social Simulations, Epistemology, Validation, Simulation Methods
Abstract: The paper relates virtual dialogues about social simulation, with the implicit reference to Galieo\'s \'dialogues concerning two new sciences\'.

István Back and Andreas Flache
Journal of Artificial Societies and Social Simulation 9 (1) 12

Kyeywords: Interpersonal Commitment, Fairness, Reciprocity, Agent-Based Simulation, Help Exchange, Evolution
Abstract: A prominent explanation of cooperation in repeated exchange is reciprocity (e.g. Axelrod, 1984). However, empirical studies indicate that exchange partners are often much less intent on keeping the books balanced than Axelrod suggested. In particular, there is evidence for commitment behavior, indicating that people tend to build long-term cooperative relationships characterised by largely unconditional cooperation, and are inclined to hold on to them even when this appears to contradict self-interest. Using an agent-based computational model, we examine whether in a competitive environment commitment can be a more successful strategy than reciprocity. We move beyond previous computational models by proposing a method that allows to systematically explore an infinite space of possible exchange strategies. We use this method to carry out two sets of simulation experiments designed to assess the viability of commitment against a large set of potential competitors. In the first experiment, we find that although unconditional cooperation makes strategies vulnerable to exploitation, a strategy of commitment benefits more from being more unconditionally cooperative. The second experiment shows that tolerance improves the performance of reciprocity strategies but does not make them more successful than commitment. To explicate the underlying mechanism, we also study the spontaneous formation of exchange network structures in the simulated populations. It turns out that commitment strategies benefit from efficient networking: they spontaneously create a structure of exchange relations that ensures efficient division of labor. The problem with stricter reciprocity strategies is that they tend to spread interaction requests randomly across the population, to keep relations in balance. During times of great scarcity of exchange partners this structure is inefficient because it generates overlapping personal networks so that often too many people try to interact with the same partner at the same time.

Matteo Richiardi, Roberto Leombruni, Nicole J. Saam and Michele Sonnessa
Journal of Artificial Societies and Social Simulation 9 (1) 15

Kyeywords: Agent-Based, Simulations, Methodology, Calibration, Validation, Sensitivity Analysis
Abstract: Traditional (i.e. analytical) modelling practices in the social sciences rely on a very well established, although implicit, methodological protocol, both with respect to the way models are presented and to the kinds of analysis that are performed. Unfortunately, computer-simulated models often lack such a reference to an accepted methodological standard. This is one of the main reasons for the scepticism among mainstream social scientists that results in low acceptance of papers with agent-based methodology in the top journals. We identify some methodological pitfalls that, according to us, are common in papers employing agent-based simulations, and propose appropriate solutions. We discuss each issue with reference to a general characterization of dynamic micro models, which encompasses both analytical and simulation models. In the way, we also clarify some confusing terminology. We then propose a three-stage process that could lead to the establishment of methodological standards in social and economic simulations.

Jill Bigley Dunham
Journal of Artificial Societies and Social Simulation 9 (1) 3

Kyeywords: Epidemiology, Social Networks, Agent-Based Simulation, MASON Toolkit
Abstract: This paper outlines the design and implementation of an agent-based epidemiological simulation system. The system was implemented in the MASON toolkit, a set of Java-based agent-simulation libraries. This epidemiological simulation system is robust and extensible for multiple applications, including classroom demonstrations of many types of epidemics and detailed numerical experimentation on a particular disease. The application has been made available as an applet on the MASON web site, and as source code on the author\'s web site.

Andreas Schlosser, Marco Voss and Lars Brückner
Journal of Artificial Societies and Social Simulation 9 (1) 4

Kyeywords: Reputation System, Trust, Formalization, Simulation
Abstract: Reputation systems evolve as a mechanism to build trust in virtual communities. In this paper we evaluate different metrics for computing reputation in multi-agent systems. We present a formal model for describing metrics in reputation systems and show how different well-known global reputation metrics are expressed by it. Based on the model a generic simulation framework for reputation metrics was implemented. We used our simulation framework to compare different global reputation systems to find their strengths and weaknesses. The strength of a metric is measured by its resistance against different threat-models, i.e. different types of hostile agents. Based on our results we propose a new metric for reputation systems.

Kees Zoethout, Wander Jager and Eric Molleman
Journal of Artificial Societies and Social Simulation 9 (1) 5

Kyeywords: Organisation, Task Rotation, Work Groups, Psychological Theory, Multi Agent Simulation
Abstract: In work groups, task rotation may decrease the negative consequences of boredom and lead to a better task performance. In this paper we use multi agent simulation to study several organisation types in which task rotation may or may not emerge. By looking at the development of expertise and motivation of the different agents and their performance as a function of self-organisation, boredom, and task rotation frequency, we describe the dynamics of task rotation. The results show that systems in which task rotation emerges perform better than systems in which the agents merely specialise in one skill. Furthermore, we found that under certain circumstances, a task that leads to a high degree of boredom was performed better than a task causing a low level of boredom.

Peter Andras, John Lazarus, Gilbert Roberts and Steven J Lynden
Journal of Artificial Societies and Social Simulation 9 (1) 7

Kyeywords: Agent-Based Modelling, Cooperation, Social Interaction Simulation, Uncertainty
Abstract: Uncertainty is an important factor that influences social evolution in natural and artificial environments. Here we distinguish between three aspects of uncertainty. Environmental uncertainty is the variance of resources in the environment, perceived uncertainty is the variance of the resource distribution as perceived by the organism and effective uncertainty is the variance of resources effectively enjoyed by individuals. We show analytically that perceived uncertainty is larger than environmental uncertainty and that effective uncertainty is smaller than perceived uncertainty, when cooperation is present. We use an agent society simulation in a two dimensional world for the generation of simulation data as one realisation of the analytical results. Together with our earlier theoretical work, results here show that cooperation can buffer the detrimental effects of uncertainty on the organism. The proposed conceptualisation of uncertainty can help in understanding its effects on social evolution and in designing artificial social environments.

Derek Gatherer
Journal of Artificial Societies and Social Simulation 9 (2) 1

Kyeywords: Simulation, Perl, Eurovision Song Contest, Voting Blocs, Collusive Voting
Abstract: The voting patterns in the Eurovision Song Contest have attracted attention from various researchers, spawning a small cross-disciplinary field of what might be called 'eurovisiopsephology' incorporating insights from politics, sociology and computer science. Although the outcome of the contest is decided using a simple electoral system, its single parameter - the number of countries casting a vote - varies from year to year. Analytical identification of statistically significant trends in voting patterns over a period of several years is therefore mathematically complex. Simulation provides a method for reconstructing the contest's history using Monte Carlo methods. Comparison of simulated histories with the actual history of the contest allows the identification of statistically significant changes in patterns of voting behaviour, without requiring a full mathematical solution. In particular, the period since the mid-90s has seen the emergence of large geographical voting blocs from previously small voting partnerships, which initially appeared in the early 90s. On at least two occasions, the outcome of the contest has been crucially affected by voting blocs. The structure of these blocs implies that a handful of centrally placed countries have a higher probability of being future winners.

Monojit Choudhury, Anupam Basu and Sudeshna Sarkar
Journal of Artificial Societies and Social Simulation 9 (2) 2

Kyeywords: Language Change, Linguistic Agent, Language Game, Multi-Agent Simulation, Schwa Deletion
Abstract: Recently, there has been a revival of interest in multi-agent simulation techniques for exploring the nature of language change. However, a lack of appropriate validation of simulation experiments against real language data often calls into question the general applicability of these methods in modeling realistic language change. We try to address this issue here by making an attempt to model the phenomenon of schwa deletion in Hindi through a multi-agent simulation framework. The pattern of Hindi schwa deletion and its diachronic nature are well studied, not only out of general linguistic inquiry, but also to facilitate Hindi grapheme-to-phoneme conversion, which is a preprocessing step to text-to-speech synthesis. We show that under certain conditions, the schwa deletion pattern observed in modern Hindi emerges in the system from an initial state of no deletion. The simulation framework described in this work can be extended to model other phonological changes as well.

Tibor Bosse and Jan Treur
Journal of Artificial Societies and Social Simulation 9 (2) 6

Kyeywords: Collective Intelligence, Simulation, Logical Formalisation, Single Vs. Multi-Agent Behaviour
Abstract: In this paper the question is addressed to what extent the collective processes in a multi-agent society can be interpreted as single agent processes. This question is answered by formal analysis and simulation. It is shown for an example process how it can be conceptualised, formalised and simulated in two different manners: from a single agent (or cognitive) and from a multi-agent (or social) perspective. Moreover, it is shown how an ontological mapping can be formally defined between the two formalisations, and how this mapping can be extended to a mapping of dynamic properties. Thus it is shown how collective behaviour can be interpreted in a formal manner as single agent behaviour.

Magda Fontana
Journal of Artificial Societies and Social Simulation 9 (2) 8

Kyeywords: Social Simulation, Economic Theory, User Community
Abstract: This paper presents the analysis of a dataset of publications in economics that makes use of simulations. Data areas explored in order to obtain information about diffusion of simulation techniques in time and across sub-disciplines. Moreover, following Robert Axelrod\'s concerns about the difficulties in sharing simulation models and their outputs, some peculiarities in the communication process among \'simulators\' are highlighted.

Juliette Rouchier and Sophie Thoyer
Journal of Artificial Societies and Social Simulation 9 (3) 1

Kyeywords: Lobbying, Europe, GMO, Multi-Agent Simulation, Public Choice, Politician, Voter, Group Contest
Abstract: The paper presents a multi-agent model simulating a two-level public decision game in which politicians, voters and interest groups interact. The objective is to model the political market for influence at the domestic level and at the international level, and to assess how new consultation procedures affect the final decision. It is based on public choice theory as well as on political science findings. We consider in this paper that lobbying groups have different strategies for influencing voters and decision-makers, with long-term and short-term effects. Our computational model enables us to represent the situation as an iterative process, in which past decisions have an impact on the preferences and choices of agents in the following period. In the paper, the model is applied to the European decision-making procedure for authorizing the placing on the market of Genetically Modified Organisms (GMO). It illustrates the political links between public opinions, lobbying groups and elected representatives at the national scale in the 15 country members, and at the European scale. It compares the procedure which was defined by the European 1990/220 Directive in 1990 with the new procedure, the 2001/18 Directive, which replaced it in 2001. The objective is to explore the impact of the new decision rules and the reinforced public participation procedures planned by the 2001/18 Directive on the lobbying efficiency of NGOs and biotechnology firms, and on the overall acceptability of the European decision concerning the release of new GMOs on the European territory.

Hans-Joachim Mosler
Journal of Artificial Societies and Social Simulation 9 (3) 4

Kyeywords: Social Influences, Persuasion Processes, Group Processes, Minority Influence, Computer Simulation, Modelling, Theory Verification, Simulation Experiments
Abstract: Very often in the history of mankind, social changes took place because a minority was successful in persuading the dominant majority of a new idea. Social psychology provides empirically well-founded theories of social influence that can explain the power of minorities at individual level. In this contribution, we present an agent-based computer simulation of one such theory, the Elaboration Likelihood Model (ELM). After introducing the theoretical background and our agent model, we present three simulation experiments that confirm past laboratory research but also go beyond its findings by adopting the method of computer simulation. First, we found that even a minority with low argument quality can be successful as long as it has positive peripheral cues. Second, our results suggest that a higher personal relevance of a topic for the majority led it to be more receptive to minority influence only when the minority showed neutral peripheral cues and very good arguments. Third, we found evidence that a neutral or only slightly biased majority is influenced more easily than a strongly biased one. To sum up, we consider these results to illustrate the notion that a well-presented, comprehensible and valid computer simulation provides a useful tool for theory development and application in an exploratory manner as long as it is well founded in terms of the model and theory.

Chengling Gou
Journal of Artificial Societies and Social Simulation 9 (3) 6

Kyeywords: Financial Markets, Simulation, Minority Game, Mix-Game
Abstract: This paper studies the simulation of financial markets using an agent-based mix-game model which is a variant of the minority game (MG). It specifies the spectra of parameters of mix-game models that fit financial markets by investigating the dynamic behaviors of mix-game models under a wide range of parameters. The main findings are (a) in order to approach efficiency, agents in a real financial market must be heterogeneous, boundedly rational and subject to asymmetric information; (b) an active financial market must be dominated by agents who play a minority game; otherwise, the market would die; (c) the system could be stable if agents who play a majority game have a faster learning rate than those who play a minority game; otherwise, the system could be unstable. The paper then induces the rules for simulating financial markets with mix-game models and gives an example. Finally, the appendix of this paper presents background information about \'El Farol bar\', MG and mix-games.

Luis R. Izquierdo and J. Gareth Polhill
Journal of Artificial Societies and Social Simulation 9 (4) 4

Kyeywords: Floating Point Arithmetic, Floating Point Errors, Agent Based Modelling, Computer Modelling, Replication
Abstract: This paper provides a framework that highlights the features of computer models that make them especially vulnerable to floating-point errors, and suggests ways in which the impact of such errors can be mitigated. We focus on small floating-point errors because these are most likely to occur, whilst still potentially having a major influence on the outcome of the model. The significance of small floating-point errors in computer models can often be reduced by applying a range of different techniques to different parts of the code. Which technique is most appropriate depends on the specifics of the particular numerical situation under investigation. We illustrate the framework by applying it to six example agent-based models in the literature.

Lilian N. Alessa, Melinda Laituri and C. Michael Barton
Journal of Artificial Societies and Social Simulation 9 (4) 6

Kyeywords: Community-Based Complex Models, Mathematics, Social Sciences
Abstract: To date, many communities of practice (COP) in the social sciences have been struggling with how to deal with rapidly growing bodies of information. Many CoPs across broad disciplines have turned to community frameworks for complexity modeling (CFCMs) but this strategy has been slow to be discussed let alone adopted by the social sciences communities of practice (SS-CoPs). In this paper we urge the SS-CoPs that it is timely to develop and establish a CBCF for the social sciences for two major reasons: the rapid acquisition of data and the emergence of critical cybertools which can facilitate agent-based, spatially-explicit models. The goal of this paper is not to prescribe how a CFCM might be set up but to suggest of what components it might consist and what its advantages would be. Agent based models serve the establishment of a CFCM because they allow robust and diverse inputs and are amenable to output-driven modifications. In other words, as phenomena are resolved by a SS-CoP it is possible to adjust and refine ABMs (and their predictive ability) as a recursive and collective process. Existing and emerging cybertools such as computer networks, digital data collections and advances in programming languages mean the SS-CoP must now carefully consider committing the human organization to enabling a cyberinfrastructure tool. The combination of technologies with human interfaces can allow scenarios to be incorporated through 'if' 'then' rules and provide a powerful basis for addressing the dynamics of coupled and complex social ecological systems (cSESs). The need for social scientists to be more engaged participants in the growing challenges of characterizing chaotic, self-organizing social systems and predicting emergent patterns makes the application of ABMs timely. The enabling of a SS-CoP CFCM human-cyberinfrastructure represents an unprecedented opportunity to synthesize, compare and evaluate diverse sociological phenomena as a cohesive and recursive community-driven process.

Paul Guyot and Shinichi Honiden
Journal of Artificial Societies and Social Simulation 9 (4) 8

Kyeywords: Agent-Based Participatory Simulations, Multi-Agent Systems, Role-Playing Games, Validation, Negotiation Support Tool
Abstract: In 2001, Olivier Barreteau proposed to jointly use multi-agent systems and role-playing games for purposes of research, training and negotiation support in the field of renewable resource management. This joint use was later labeled the "MAS/RPG methodology" and this approach is one of the foundation stones of the ComMod movement. In this article, we present an alternative method called "agent-based participatory simulations". These simulations are multi-agent systems where human participants control some of the agents. The experiments we conducted prove that it is possible to successfully merge multi-agent systems and role-playing games. We argue that agent-based participatory simulations are also a significant improvement over the MAS/RPG approach, opening new perspectives and solving some of the problems generated by the joint use of role-playing games and multi-agent systems. The advantages are at least threefold. Because all interactions are computer mediated, they can be recorded and this record can be processed and used to improve the understanding of participants and organizers alike. Because of the merge, agent-based participatory simulations decrease the distance between the agent-based model and the behavior of participants. Agent-based participatory simulations allow for computer-based improvements such as the introduction of eliciting assistant agents with learning capabilities.

Bin Hu and Debing Zhang
Journal of Artificial Societies and Social Simulation 10 (1) 1

Kyeywords: Cellular Automata; Qualitative Simulation; Group Behavior; Loyalty-Cost Equilibrium; Loyalty Gravitation; Cost Gravitation
Abstract: A cellular automata based qualitative simulation of group behavior (referred hitherto as \'loyalty to group\') will be presented by integrating QSIM (Qualitative SIMulation) and CA (Cellular Automata) modeling. First, we provide a breakdown of the structure of a group and offer an analysis of how this structure impacts behavior. The characteristics and impact had by anomalies within a group and by environmental factors are also explored. Second, we explore the transition between cause and effect (referred hitherto as the \'transition rule\') and the change in behavior that is the result of this transition (referred hitherto as the \'successor behavior state\'). A filter for weeding out anomalies is then proposed. The simulation engine is then used integrating all relevant data as outlined above. A concept referred to as the \'Loyalty-cost equilibrium\' is presented and factored into the filter. Third, the validity of this method is tested by running the simulation using eight generalized examples. The input-output of each simulation run using these examples is consistent with what can reasonably be accepted to be true, thus demonstrating that the proposed method is valid. At this point we illustrate how the simulation is applied in context. Simulation outputs (effect on group behavior) at each time stage of two alternating changes in policy are compared to determine which policy would be the most advantageous. This demonstrates that this method serves as reliable virtual tool in the decision making difficulties of group management.

Thomas Malsch and Ingo Schulz-Schaeffer
Journal of Artificial Societies and Social Simulation 10 (1) 11

Kyeywords: Socionics, Sociology, Multi-Agent Systems, Artificial Social Systems, Hybrid Systems, Social Simulation
Abstract: Socionics is an interdisciplinary approach with the objective to use sociological knowledge about the structures, mechanisms and processes of social interaction and social communication as a source of inspiration for the development of multi-agent systems, both for the purposes of engineering applications and of social theory construction and social simulation. The approach has been spelled out from 1998 on within the Socionics priority program funded by the German National research foundation. This special issue of the JASSS presents research results from five interdisciplinary projects of the Socionics program. The introduction gives an overview over the basic ideas of the Socionics approach and summarizes the work of these projects.

Klaus Jaffe and Roberto Cipriani
Journal of Artificial Societies and Social Simulation 10 (1) 7

Kyeywords: Social Simulation, Interactions, Group Size, Selfish Heard, Cultural Evolution, Biological Evolution
Abstract: A one dimensional cellular automata model describes the evolutionary dynamics of cooperation when grouping by cooperators provides protection against predation. It is used to compare the dynamics of evolution of cooperation in three settings. G: only vertical transmission of information is allowed, as an analogy of genetic evolution with heredity; H: only horizontal information transfer is simulated, through diffusion of the majority\'s opinion, as an analogy of opinion dynamics or social learning; and C: analogy of cultural evolution, where information is transmitted both horizontally (H) and vertically (V) so that learned behavior can be transmitted to offspring. The results show that the prevalence of cooperative behavior depends on the costs and benefits of cooperation so that: a- cooperation becomes the dominant behavior, even in the presence of free-riders (i.e., non-cooperative obtaining benefits from the cooperation of others), under all scenarios, if the benefits of cooperation compensate for its cost; b- G is more susceptible to selection pressure than H achieving a closer adaptation to the fitness landscape; c- evolution of cooperative behavior in H is less sensitive to the cost of cooperation than in G; d- C achieves higher levels of cooperation than the other alternatives at low costs, whereas H does it at high costs. The results suggest that a synergy between H and V is elicited that makes the evolution of cooperation much more likely under cultural evolution than under the hereditary kind where only V is present.

J. Gareth Polhill, Edoardo Pignotti, Nicholas M. Gotts, Pete Edwards and Alun Preece
Journal of Artificial Societies and Social Simulation 10 (2) 2

Kyeywords: Agent-Based Social Simulation, Experiments, Ontologies, Replication, Semantic Grid
Abstract: Agent-based models, perhaps more than other models, feature large numbers of parameters and potentially generate vast quantities of results data. This paper shows through the FEARLUS-G project (an ESRC e-Social Science Initiative Pilot Demonstrator Project) how deploying an agent-based model on the Semantic Grid facilitates international collaboration on investigations using such a model, and contributes to establishing rigorous working practices with agent-based models as part of good science in social simulation. The experimental workflow is described explicitly using an ontology, and a Semantic Grid service with a web interface implements the workflow. Users are able to compare their parameter settings and results, and relate their work with the model to wider scientific debate.

Wim Westera
Journal of Artificial Societies and Social Simulation 10 (2) 5

Kyeywords: Distance Learning, Computational Simulations, System Dynamics, Education and Application, Peer Support, Peer Allocation
Abstract: This paper proposes a computational model for the allocation of fleeting peer tutors in a community of learners: a student\'s call for support is evaluated by the model in order to allocate the most appropriate peer tutor. Various authors have suggested peer tutoring as a favourable approach for confining the ever-growing workloads of teachers and tutors in online learning environments. The model\'s starting point is to serve two conflicting requirements: 1) the allocated peers should have sufficient knowledge to guarantee high quality support and 2) tutoring workload of peers should be fairly distributed over the student population. While the first criterion is likely to saddle a small number of very bright students with all the tutoring workload, the unconditional pursuit of a uniform workload distribution over the students is likely to allocate incompetent tutors. In both cases the peer support mechanism is doomed to failure. The paper identifies relevant variables and elaborates an allocation procedure that combines various filter types. The functioning of the allocation procedure is tested through a computer simulation program that has been developed to represent the student population, the students curriculum and the dynamics of tutor allocation. The current study demonstrates the feasibility of the self-allocating peer tutoring mechanism. The proposed model is sufficiently stable within a wide range of conditions. By introducing an overload tolerance parameter which stretches the fair workload distribution criteria, substantial improvements of the allocation success rate are effected. It is demonstrated that the allocation algorithm works best at large population sizes. The results show that the type of curriculum (collective route or individualised routes) has only little influence on the allocation mechanism.

Gilbert Peffer and Barbara Llacay
Journal of Artificial Societies and Social Simulation 10 (2) 6

Kyeywords: Financial Markets, Multi-Agent Simulation, Performativity, Higher-Order Strategies
Abstract: The trading and investment decision processes in financial markets become ever more dependent on the use of valuation and risk models. In the case of risk management for instance, modelling practice has become quite homogeneous and the question arises as to the effect this has on the price formation process. Furthermore, sophisticated investors who have private information about the use and characteristics of these models might be able to make superior gains in such an environment. The aim of this article is to test this hypothesis in a stylised market, where a strategic investor trades on information about the valuation and risk management models used by other market participants. Simulation results show that under certain market conditions, such a \'higher-order\' strategy generates higher profits than standard fundamental and momentum strategies that do not draw on information about model use.

Arvid Oskar Ivar Hoffmann, Wander Jager and J. H. Von Eije
Journal of Artificial Societies and Social Simulation 10 (2) 7

Kyeywords: Agent-Based Computational Finance, Artificial Stock Markets, Behavioral Finance, Micro-Macro Links, Multi-Agent Simulation, Stock Market Characteristics
Abstract: This paper studies the use of social simulation in linking micro level investor behaviour and macro level stock market dynamics. Empirical data from a survey on individual investors\' decision-making and social interaction was used to formalize the trading and interaction rules of the agents of the artificial stock market SimStockExchange. Multiple simulation runs were performed with this artificial stock market, which generated macro level results, like stock market prices and returns over time. These outcomes were subsequently compared to empirical macro level data from real stock markets. Partial qualitative as well as quantitative agreement between the simulated asset returns distributions and the asset returns distributions of the real stock markets was found.

Paul Windrum, Giorgio Fagiolo and Alessio Moneta
Journal of Artificial Societies and Social Simulation 10 (2) 8

Kyeywords: Methodology, Empirical Validation, Agent-Based Models, Simulation, Calibration, History-Friendly Models
Abstract: This paper addresses a set of methodological problems arising in the empirical validation of agent-based (AB) economics models and discusses how these are currently being tackled. These problems are generic for all those engaged in AB modelling, not just economists. The discussion is therefore of direct relevance to JASSS readers. The paper has two objectives. The first objective is the identification of a set of issues that are common to all modellers engaged in empirical validation. This gives rise to a novel taxonomy that captures the relevant dimensions along which AB modellers differ. The second objective is a focused discussion of three alternative methodological approaches being developed in AB economics - indirect calibration, the Werker-Brenner approach, and the history-friendly approach – and a set of (as yet) unresolved issues for empirical validation that require future research.

Xiaoguang Gong and Renbin Xiao
Journal of Artificial Societies and Social Simulation 10 (3) 1

Kyeywords: Multi-Agent Simulation, News Spread, Small World Network , Epidemic
Abstract: The spread of news about an epidemic can easily lead to a social panic. In order to devise measures to control such a panic, it is necessary to consider characteristics of the spread of epidemic news, based on mechanisms at the individual level. In this paper, first, some features of multi-agent simulation are reviewed. Then a multi-agent simulation model of epidemic news spread (ENS) is designed and realized. Based on simulation experiments and sensitivity analyses, the influence of social relationships, the degree of trust in news of the epidemic, the epidemic spread intensity and the network structure of the epidemic news spread are studied. The research results include: (1) As the number of social relationships increases, the rate of spread of epidemic news rapidly rises, and the ratio of people who have heard the news directly decreases. The result is that the \'radiation effect\' of the epidemic news spread will be enhanced when the number of social relationships increases. (2) With the increase of the degree of trust in the news, the rate of spread of the news will also rapidly increase, but variation in the ratio of the people who have heard the news directly is not significant. This means that the \'radiation effect\' of the spread of the news does not change much more in relation to the degree of trust in the epidemic news. (3) The ratio of the people who have heard the news directly increases when the infection range increases (i.e. the spread intensity of epidemic increases), and vice versa. But the variation of the speed of the epidemic news spread is not significant. (4) When the network structure is assumed to be a small world network, the spread speed will be slower than that in a random network with the same average vertex degree and the forgetting speed will be faster than that in a random network with the same average vertex degree.

J. Gareth Polhill and Bruce Edmonds
Journal of Artificial Societies and Social Simulation 10 (3) 10

Kyeywords: Agent-Based Social Simulation, Replication, Software Licences, Documentation, Archiving
Abstract: We consider here issues of open access to social simulations, with a particular focus on software licences, though also briefly discussing documentation and archiving. Without any specific software licence, the default arrangements are stipulated by the Berne Convention (for those countries adopting it), and are unsuitable for software to be used as part of the scientific process (i.e. simulation software used to generate conclusions that are to be considered part of the scientific domain of discourse). Without stipulating any specific software licence, we suggest rights that should be provided by any candidate licence for social simulation software, and provide in an appendix an evaluation of some popularly used licences against these criteria.

Laurent Tambayong
Journal of Artificial Societies and Social Simulation 10 (3) 2

Kyeywords: Dynamics, Network, Game Theory, Model,Simulation, Equilibrium, Complexity
Abstract: This article studies the dynamics in the formation processes of a mutual consent network in game theory setting: the Co-Author Model. In this article, a limited observation is applied and analytical results are derived. Then, 2 parameters are varied: the number of individuals in the network and the initial probability of the links in the network in its initial state. A simulation result shows a finding that is consistent with an analytical result for a state of equilibrium while it also shows different possible equilibria.

Jijun Zhao, Ferenc Szidarovszky and Miklos N. Szilagyi
Journal of Artificial Societies and Social Simulation 10 (3) 3

Kyeywords: Agent-Based Simulation, N-Person Games, Structure Analysis, Equilibrium
Abstract: The purpose of this study is to present a systematic analysis of the long-term behavior of the agents of an artificial society under varying payoff functions in finite neighborhood binary games. By assuming the linearity of the payoffs of both cooperating and defecting agents, the type of the game is determined by four fundamental parameters. By fixing the values of three of them and systematically varying the fourth one we can observe a transition from Prisoner\'s Dilemma to Leader Game through Chicken and Benevolent Chicken Games. By using agent-based simulation we are able to observe the long-term behavior of the artificial society with different and gradually changing payoff structure. The difference between different games is explored and the effect of the transition from one game to the other on the society is investigated. The results depend on the personality types of the agents. In this study greedy and Pavlovian agents are considered. In the first case, we observe the most significant change in trajectory structure between Prisoner\'s Dilemma and Chicken Games showing significant difference in the behavioral patterns of the agents. Almost no changes can be observed between Benevolent Chicken and Leader Games, and only small change between Chicken and Benevolent Chicken. The trajectories change from always converging to regularly oscillating patterns with systematically altering amplitude and central values. The results are very similar whether the agents consider themselves as members of their neighborhoods or not. With Pavlovian agents no significant difference can be observed between the four games, the trajectories always converge and the limits smoothly and monotonically depend on the value of the varying parameter.

Jean-Philippe Cointet and Camille Roth
Journal of Artificial Societies and Social Simulation 10 (3) 5

Kyeywords: Agent-Based Simulation, Complex Systems, Empirical Calibration and Validation, Knowledge Diffusion, Model Comparison, Social Networks
Abstract: Knowledge diffusion models typically involve two main features: an underlying social network topology on one side, and a particular design of interaction rules driving knowledge transmission on the other side. Acknowledging the need for realistic topologies and adoption behaviors backed by empirical measurements, it becomes unclear how accurately existing models render real-world phenomena: if indeed both topology and transmission mechanisms have a key impact on these phenomena, to which extent does the use of more or less stylized assumptions affect modeling results? In order to evaluate various classical topologies and mechanisms, we push the comparison to more empirical benchmarks: real-world network structures and empirically measured mechanisms. Special attention is paid to appraising the discrepancy between diffusion phenomena (i) on some real network topologies vs. various kinds of scale-free networks, and (ii) using an empirically-measured transmission mechanism, compared with canonical appropriate models such as threshold models. We find very sensible differences between the more realistic settings and their traditional stylized counterparts. On the whole, our point is thus also epistemological by insisting that models should be tested against simulation-based empirical benchmarks.

Stéphane Airiau, Sabyasachi Saha and Sandip Sen
Journal of Artificial Societies and Social Simulation 10 (3) 7

Kyeywords: Repeated Games, Evolution, Simulation
Abstract: Evolutionary tournaments have been used effectively as a tool for comparing game-playing algorithms. For instance, in the late 1970's, Axelrod organized tournaments to compare algorithms for playing the iterated prisoner's dilemma (PD) game. These tournaments capture the dynamics in a population of agents that periodically adopt relatively successful algorithms in the environment. While these tournaments have provided us with a better understanding of the relative merits of algorithms for iterated PD, our understanding is less clear about algorithms for playing iterated versions of arbitrary single-stage games in an environment of heterogeneous agents. While the Nash equilibrium solution concept has been used to recommend using Nash equilibrium strategies for rational players playing general-sum games, learning algorithms like fictitious play may be preferred for playing against sub-rational players. In this paper, we study the relative performance of learning and non-learning algorithms in an evolutionary tournament where agents periodically adopt relatively successful algorithms in the population. The tournament is played over a testbed composed of all possible structurally distinct 2×2 conflicted games with ordinal payoffs: a baseline, neutral testbed for comparing algorithms. Before analyzing results from the evolutionary tournament, we discuss the testbed, our choice of representative learning and non-learning algorithms and relative rankings of these algorithms in a round-robin competition. The results from the tournament highlight the advantage of learning algorithms over players using static equilibrium strategies for repeated plays of arbitrary single-stage games. The results are likely to be of more benefit compared to work on static analysis of equilibrium strategies for choosing decision procedures for open, adapting agent society consisting of a variety of competitors.

James F. Robison-Cox, Richard F. Martell and Cynthia G. Emrich
Journal of Artificial Societies and Social Simulation 10 (3) 8

Kyeywords: Glass Ceiling, Gender Stratification, Promotion, Performance Evaluation Bias, Computer Simulation
Abstract: The simulation of promotional competitions in corporations described herein allows comparisons of suggested reasons for the paucity of women in the highest level of corporate management. Runs with small, medium and large-sized companies all give similar results. The strongest effect is evidenced when men are given a bonus in performance evaluations. Similar stratification is observed when men's scores are drawn from a distribution with increased variance. Other explanations (increased female attrition, career delays for women, line-staff divisions, and external labor market) do not, by themselves produce strong gender stratification, but could add to that produced by biased evaluations.

Onofrio Gigliotta, Orazio Miglino and Domenico Parisi
Journal of Artificial Societies and Social Simulation 10 (4) 1

Kyeywords: Agent Based Models, Leaders, Social Simulation, Social Structure, Communication Topologies
Abstract: We describe simulations of groups of agents that have to reach a target in a two dimensional environment, the performance criterion being the time taken by the last agent to reach the target. If the target is within a given distance from the agent, the agent moves towards the target; otherwise it moves randomly. The simulations contrast groups with and without a leader, where a leader is a member of the group which other members of the group follow as it moves through the environment. We investigate three factors that affect group performance: (1) group size; (2) the presence or absence of an individual agent with the ability to detect targets at a greater distance than those \'visible\' to its companions; (3) the existence of a communication network among group members. The results show that, in groups without communication, leaders have a beneficial effect on group performance, especially in large groups and if the individual with better than average sensory capabilities is the leader of the group. However, in situations where group members can communicate, these results are reversed, with leaders being detrimental, rather than beneficial, to group performance

Roy Wilson
Journal of Artificial Societies and Social Simulation 10 (4) 4

Kyeywords: Social Influence; Decision Processes; Social Networks; Group Dynamics; Simulation; Agent-Based Modeling
Abstract: This paper describes a simulation study of decision-making. It is based on a model of social influence in small, task-oriented, groups. A process model of dyadic social influence is built on top of a dynamic model of status and task participation that describes the emergence of a stable power and prestige order. Two models of group decision-making are examined: a static model for which the beliefs of actors do not change, and a process model for which they do as a function of the standing of each member of each interacting pair in the evolving power and prestige order. The models are compared on a set of N=111 cases, each requiring an affirmative or negative group response to a proposition A(c) that pertains to a case c. Initial beliefs are assigned to each of five members of distinct professions based on an analysis of independently collected behavioral data pertinent to the proposition to be affirmed or denied in each case. Although the two influence models yield identical decisions in 70% of the cases examined, the differences between them are statistically significant and in several instances show a medium effect size. Most importantly, the differences can be explained in terms of social influence and the status and task participation model on which it depends.

Minh Nguyen-Duc and Alexis Drogoul
Journal of Artificial Societies and Social Simulation 10 (4) 5

Kyeywords: Participatory Social Simulations, Agent-Based Social Simulations, Computational Agents, Role-Playing Games, Artificial Maieutics, User-Centered Design
Abstract: In social science, the role of stakeholders is increasing in the development and use of simulation models. Their participation in the design of agent-based models (ABMs) has widely been considered as an efficient solution to the validation of this particular type of model. Traditionally, "agents" (as basic model elements) have not been concerned with stakeholders directly but via designers or role-playing games (RPGs). In this paper, we intend to bridge this gap by introducing computational or software agents, implemented from an initial ABM, into a new kind of RPG, mediated by computers, so that these agents can interact with stakeholders. This interaction can help not only to elicit stakeholders' informal knowledge or unpredicted behaviours, but also to control stakeholders' focus during the games. We therefore formalize a general participatory design method using software agents, and illustrate it by describing our experience in a project aimed at developing agent-based social simulations in the field of air traffic management.

Anthony Dekker
Journal of Artificial Societies and Social Simulation 10 (4) 6

Kyeywords: Network Rewiring, Small World Networks, Self-Synchronization, Agent Simulation, Collaboration, Problem Solving
Abstract: The behaviour of many complex systems is influenced by the underlying network topology. In particular, this applies to social systems in which people or organisational units collaboratively solve problems. Network rewiring processes are one useful tool in understanding the relationship between network topology and behaviour. Here we use the Kawachi network rewiring process, together with three simple simulation models of organisational collaboration, to investigate the network characteristics that influence performance. The simulation models are based on the Assignment Problem, the Kuramoto Model from physics, and a novel model of collaborative problem-solving which involves finding numbers with certain characteristics, the existence of which is guaranteed by Lagrange\'s Theorem. For all three models, performance is best when the underlying organisational network has a low average distance between nodes. In addition, the third model identified long-range connectivity between nodes as an important predictor of performance. The commonly-used clustering coefficient, which is a measure of short-range connectivity, did not affect performance. We would expect that long-range network connectivity would also influence the behaviour of other complex systems displaying global self-synchronization. The paper also demonstrates the utility of simple computational models in studying issues of organisational topology.

Shah Jamal Alam, Ruth Meyer, Gina Ziervogel and Scott Moss
Journal of Artificial Societies and Social Simulation 10 (4) 7

Kyeywords: Agent-Based Social Simulation, Evidence-Driven Modeling, Socioeconomic Stressors, HIV/AIDS Impact
Abstract: In this paper, we present an agent-based simulation model of the social impacts of HIV/AIDS in villages in the Sekhukhune district of the Limpopo province in South Africa. AIDS is a major concern in South Africa, not just in terms of disease spread but also in term of its impact on society and economic development. The impact of the disease cannot however be considered in isolation from other stresses, such as food insecurity, high climate variability, market fluctuations and variations in support from government and non-government sources. The model described in this paper focuses on decisions made at the individual and household level, based upon evidence from detailed case studies, and the different types of networks between these players that influence their decision making. Key to the model is that these networks are dynamic and co-evolving, something that has rarely been considered in social network analysis. The results presented here demonstrate how this type of simulation can aid better understanding of this complex interplay of issues. In turn, we hope that this will prove to be a powerful tool for policy development.

Phillip Stroud, Sara Del Valle, Stephen Sydoriak, Jane Riese and Susan Mniszewski
Journal of Artificial Societies and Social Simulation 10 (4) 9

Kyeywords: Agent Based Modeling, Computer Simulation, Epidemic Simulation, Public Health Policy
Abstract: EpiSimS is a massive simulation of the movements, activities, and social interactions of individuals in realistic synthetic populations, and of the dynamics of contagious disease spread on the resulting social contact network. This paper describes the assumptions and methodology in the EpiSimS model. It also describes and presents a simulation of the spatial dynamics of pandemic influenza in an artificial society constructed to match the demographics of southern California. As an example of the utility of the massive simulation approach, we demonstrate a strong correlation between local demographic characteristics and pandemic severity, which gives rise to previously unanticipated spatial pandemic hotspots. In particular, the average household size in a census tract is strongly correlated with the clinical attack rate computed by the simulation. Public heath agencies with responsibility for communities having relatively high population per household should expect to be more severely hit by a pandemic.

Scott Moss
Journal of Artificial Societies and Social Simulation 11 (1) 5

Kyeywords: Social Simulation, Validation, Companion Modelling, Data Generating Mechanisms, Complexity
Abstract: This paper draws on the metaphor of a spectrum of models ranging from the most theory-driven to the most evidence-driven. The issue of concern is the practice and criteria that will be appro- priate to validation of different models. In order to address this concern, two modelling approaches are investigated in some detailed – one from each end of our metaphorical spectrum. Windrum et al. (2007) (http://jasss.soc.surrey.ac.uk/10/2/8.html) claimed strong similarities between agent based social simulation and conventional social science – specifically econometric – approaches to empirical modelling and on that basis considered how econometric validation techniques might be used in empirical social simulations more broadly. An alternative is the approach of the French school of \'companion modelling\' associated with Bousquet, Barreteau, Le Page and others which engages stakeholders in the modelling and validation process. The conventional approach is con- strained by prior theory and the French school approach by evidence. In this sense they are at opposite ends of the theory-evidence spectrum. The problems for validation identified by Windrum et al. are shown to be irrelevant to companion modelling which readily incorporate complexity due to realistically descriptive specifications of individual behaviour and social interaction. The result combines the precision of formal approaches with the richness of narrative scenarios. Companion modelling is therefore found to be practicable and to achieve what is claimed for it and this alone is a key difference from conventional social science including agent based computational economics.

Ugo Merlone, Michele Sonnessa and Pietro Terna
Journal of Artificial Societies and Social Simulation 11 (2) 5

Kyeywords: Replication of Models; Model Validation; Agent-Based Simulation
Abstract: In this paper we discuss strategies concerning the implementation of an agent-based simulation of complex phenomena. The model we consider accounts for population decomposition and interaction in industrial districts. The approach we follow is twofold: on one hand, we implement progressively more complex models using different approaches (vertical multiple implementations); on the other hand, we replicate the agent-based simulation with different implementations using jESOF, JAS and plain C++ (horizontal multiple implementations). By using both different implementation approaches and a multiple implementation strategy, we highlight the benefits that arise when the same model is implemented on radically different simulation environments, comparing the advantages of multiple modeling implementations. Our findings provide some important suggestions in terms of model validation, showing how models of complex systems tend to be extremely sensitive to implementation details. Finally we point out how statistical techniques may be necessary when comparing different platform implementations of a single model.

Juliette Rouchier, Claudio Cioffi-Revilla, J. Gareth Polhill and Keiki Takadama
Journal of Artificial Societies and Social Simulation 11 (2) 8

Kyeywords: Social Simulation, Agent-Based Modelling, Comparative Computational Methodology, Validation, Replication
Abstract: [No abstract]

Keiki Takadama, Tetsuro Kawai and Yuhsuke Koyama
Journal of Artificial Societies and Social Simulation 11 (2) 9

Kyeywords: Micro- and Macro-Level Validation, Agent-Based Simulation, Agent Modeling, Sequential Bargaining Game, Reinforcement Learning
Abstract: This paper addresses both micro- and macro-level validation in agent-based simulation (ABS) to explore validated agents that can reproduce not only human-like behaviors externally but also human-like thinking internally. For this purpose, we employ the sequential bargaining game, which can investigate a change in humans' behaviors and thinking longer than the ultimatum game (i.e., one-time bargaining game), and compare simulation results of Q-learning agents employing any type of the three types of action selections (i.e., the ε-greedy, roulette, and Boltzmann distribution selections) in the game. Intensive simulations have revealed the following implications: (1) Q-learning agents with any type of three action selections can reproduce human-like behaviors but not human-like thinking, which means that they are validated from the macro-level viewpoint but not from the micro-level viewpoint; and (2) Q-learning agents employing Boltzmann distribution selection with changing the random parameter can reproduce both human-like behaviors and thinking, which means that they are validated from both micro- and macro-level viewpoints.

Dmytro Tykhonov, Catholijn Jonker, Sebastiaan Meijer and Tim Verwaart
Journal of Artificial Societies and Social Simulation 11 (3) 1

Kyeywords: Trust, Deception, Supply Chain, Multi-Agent System, Simulation
Abstract: This paper describes a multi-agent simulation model of the Trust And Tracing game. The Trust And Tracing game is a gaming simulation for human players, developed as a research tool for data collection on human behaviour in food supply chains with asymmetric information about food quality and food safety. Important issues in the game are opportunistic behaviour (deceit), trust and institutional arrangements for enforcing compliance. The goal is to improve the understanding of human decision making with respect to these issues. To this end multi-agent simulation can be applied to simulate the effect of models of individual decision making in partner selection, negotiation, deceit and trust on system behaviour. The combination of human gaming simulation and multi-agent simulation offers a basis for model refinement in a cycle of validation, experimentation, and formulation of new hypotheses. This paper describes a first round of model formulation and validation. The models presented are validated by a series of experiments performed by the implemented simulation system, of which the outcomes are compared on aggregated level to the outcomes of games played by humans. The experiments cover in a systematic way the important variations in parameter settings possible in the game and in the characteristics of the agents. The simulation results show the same tendencies of behaviour as the observed human games.

Oliver Will and Rainer Hegselmann
Journal of Artificial Societies and Social Simulation 11 (3) 3

Kyeywords: Replication, Social Dilemmas, Simulation Methodology, Cooperation, Trust, Agent-Based Modelling
Abstract: The article describes how and why we failed to replicate main effects of a computational model that Michael Macy and Yoshimichi Sato published in the Proceedings of the National Academy of Sciences (May 2002). The model is meant to answer a fundamental question about social life: Why, when and how is it possible to build trust with distant people? Based on their model, Macy and Sato warn the US society about an imminent danger: the possible break down of trust caused by too much social mobility. But the computational evidence for exactly that result turned out not to be replicable.

Yutaka NAKAI and Masayoshi Muto
Journal of Artificial Societies and Social Simulation 11 (3) 6

Kyeywords: Community, Carl Schmitt, a Friend and an Enemy, Tit for Tat, Coward, Evolutionary Simulation
Abstract: A society consisting of agents who can freely choose to attack or not to attack others inevitably evolves into a battling society (a \'war of all against all\'). We investigated whether strategies based on C. Schmitt\'s concept of the political, the distinction of a friend and an enemy, lead to the emergence and collapse of social order. Especially, we propose \'friend selection strategies\' (FSSs), one of which we called the \'us-TFT\' (tit for tat) strategy, which requires an agent to regard one who did not attack him or his \'friends\' as a \'friend\'. We carried out evolutionary simulations on an artificial society consisting of FSS agents. As a result, we found that the us-TFT results in a peaceful society with the emergence of an us-TFT community. In addition, we found that the collapse of a peaceful society is triggered by another FSS strategy called a \'coward\'.

Noam Bergman, Alex Haxeltine, Lorraine Whitmarsh, Jonathan Köhler, Michel Schilperoord and Jan Rotmans
Journal of Artificial Societies and Social Simulation 11 (3) 7

Kyeywords: Complex Systems, Agent-Based Modelling, Social Simulation, Transitions, Transition Theory
Abstract: We report on research that is developing a simulation model for assessing systemic innovations, or 'transitions', of societal systems towards a more sustainable development. Our overall aim is to outline design principles for models that can offer new insights into tackling persistent problems in large-scale systems, such as the European road transport system or the regional management of water resources. The systemic nature of these problems is associated with them being complex, uncertain and cutting across a number of sectors, and indicates a need for radical technological and behavioural solutions that address changes at the systems level rather than offering incremental changes within sub-systems. Model design is inspired by recent research into transitions, an emerging paradigm which provides a framework for tackling persistent problems. We use concepts from the literature on transitions to develop a prototype of a generic 'transition model'. Our prototype aims to capture different types of transition pathways, using historical examples such as the transition from horse-drawn carriages to cars or that from sailing ships to steam ships. The model combines agent-based modelling techniques and system dynamics, and includes interactions of individual agents and sub-systems, as well as cumulative effects on system structures. We show success in simulating different historical transition pathways by adapting the model's parameters and rules for each example. Finally, we discuss the improvements necessary for systematically exploring and detailing transition pathways in empirical case-study applications to current and future transitions such as the transition to a sustainable transport system in Europe.

Alan G. Isaac
Journal of Artificial Societies and Social Simulation 11 (3) 8

Kyeywords: Agent-Based Simulation, Python, Prisoner's Dilemma
Abstract: This paper is an introduction to agent-based simulation using the Python programming language. The core objective of the paper is to enable students, teachers, and researchers immediately to begin social-science simulation projects in a general purpose programming language. This objective is facilitated by design features of the Python programming language, which we very briefly discuss. The paper has a 'tutorial' component, in that it is enablement-focused and therefore strongly application-oriented. As our illustrative application, we choose a classic agent-based simulation model: the evolutionary iterated prisoner's dilemma. We show how to simulate the iterated prisoner's dilemma with code that is simple and readable yet flexible and easily extensible. Despite the simplicity of the code, it constitutes a useful and easily extended simulation toolkit. We offer three examples of this extensibility: we explore the classic result that topology matters for evolutionary outcomes, we show how player type evolution is affected by payoff cardinality, and we show that strategy evaluation procedures can affect strategy persistence. Social science students and instructors should find that this paper provides adequate background to immediately begin their own simulation projects. Social science researchers will additionally be able to compare the simplicity, readability, and extensibility of the Python code with comparable simulations in other languages.

Keith Christensen and Yuya Sasaki
Journal of Artificial Societies and Social Simulation 11 (3) 9

Kyeywords: Agent-Based Simulation, Individual-Based Simulation, Disability, Emergency Egress, Evacuation, Reinforcement Learning
Abstract: Catastrophic events have raised numerous issues concerning how effectively the built environment accommodates the evacuation needs of individuals with disabilities. Individuals with disabilities represent a significant, yet often overlooked, portion of the population disproportionately affected in emergency situations. Incorporating disability considerations into emergency evacuation planning, preparation, and other activities is critical. The most widely applied method used to evaluate how effectively the built environment accommodates emergency evacuations is agent-based or microsimulation modeling. However, current evacuation models do not adequately address individuals with disabilities in their simulated populations. This manuscript describes the BUMMPEE model, an agent-based simulation capable of classifying the built environment according to environmental characteristics and simulating a heterogeneous population according to variation in individual criteria. The method allows for simulated behaviors which more aptly represent the diversity and prevalence of disabilities in the population and their interaction with the built environment. Comparison of the results of an evacuation simulated using the BUMMPEE model is comparable to a physical evacuation with a similar population and setting. The results of the comparison indicate that the BUMMPEE model is a reasonable approach for simulating evacuations representing the diversity and prevalence of disability in the population

Mikola Lysenko and Roshan M. D'Souza
Journal of Artificial Societies and Social Simulation 11 (4) 10

Kyeywords: GPGPU, Agent Based Modeling, Data Parallel Algorithms, Stochastic Simulations
Abstract: Agent-based modeling is a technique for modeling dynamic systems from the bottom up. Individual elements of the system are represented computationally as agents. The system-level behaviors emerge from the micro-level interactions of the agents. Contemporary state-of-the-art agent-based modeling toolkits are essentially discrete-event simulators designed to execute serially on the Central Processing Unit (CPU). They simulate Agent-Based Models (ABMs) by executing agent actions one at a time. In addition to imposing an un-natural execution order, these toolkits have limited scalability. In this article, we investigate data-parallel computer architectures such as Graphics Processing Units (GPUs) to simulate large scale ABMs. We have developed a series of efficient, data parallel algorithms for handling environment updates, various agent interactions, agent death and replication, and gathering statistics. We present three fundamental innovations that provide unprecedented scalability. The first is a novel stochastic memory allocator which enables parallel agent replication in O(1) average time. The second is a technique for resolving precedence constraints for agent actions in parallel. The third is a method that uses specialized graphics hardware, to gather and process statistical measures. These techniques have been implemented on a modern day GPU resulting in a substantial performance increase. We believe that our system is the first ever completely GPU based agent simulation framework. Although GPUs are the focus of our current implementations, our techniques can easily be adapted to other data-parallel architectures. We have benchmarked our framework against contemporary toolkits using two popular ABMs, namely, SugarScape and StupidModel.

Michael Macy and Yoshimichi Sato
Journal of Artificial Societies and Social Simulation 11 (4) 11

Kyeywords: Replication, Social Dilemmas, Simulation Methodology, Cooperation, Trust, Agent-Based Modelling
Abstract: [No abstract]

Martin Neumann
Journal of Artificial Societies and Social Simulation 11 (4) 6

Kyeywords: Norms, Normative Agent-Based Social Simulation, Role Theory, Methodological Individualism
Abstract: This paper describes a survey of normative agent-based social simulation models. These models are examined from the perspective of the foundations of social theory. Agent-based modelling contributes to the research program of methodological individualism. Norms are a central concept in the role theoretic concept of action in the tradition of Durkheim and Parsons. This paper investigates to what extend normative agent-based models are able to capture the role theoretic concept of norms. Three methodological core problems are identified: the question of norm transmission, normative transformation of agents and what kind of analysis the models contribute. It can be shown that initially the models appeared only to address some of these problems rather than all of them simultaneously. More recent developments, however, show progress in that direction. However, the degree of resolution of intra agent processes remains too low for a comprehensive understanding of normative behaviour regulation.

Pawel Sobkowicz
Journal of Artificial Societies and Social Simulation 12 (1) 11

Kyeywords: Methodology, Agent Based Social Simulation, Qualitative Analysis; Evidence; Conditions of Application
Abstract: The growing field of studies of opinion formation using physical formalisms and computer simulation based tools suffers from relative lack of connection to the 'real world' societal behaviour. Such sociophysics research should aim at explaining observations or at proposing new ones. Unfortunately, this is not always the case, as many works concentrate more on the models themselves than on the social phenomena. Moreover, the simplifications proposed in simulations often sacrifice realism on the altar of computability. There are several ways to improve the value of the research, the most important by promoting truly multidisciplinary cooperation between physicists aiming to describe social phenomena and sociologists studying the phenomena in the field. In the specific case of modelling of opinion formation there are a few technical ideas which might bring the computer models much closer to reality, and therefore to improve the predictive value of the sociophysics approach.

Luca Arciero, Claudia Biancotti, Leandro D'Aurizio and Claudio Impenna
Journal of Artificial Societies and Social Simulation 12 (1) 2

Kyeywords: Agent-Based Modeling, Payment Systems, RTGS, Liquidity, Crisis Simulation
Abstract: This paper presents an exploratory agent-based model of a real time gross settlement (RTGS) payment system. Banks are represented as agents who exchange payment requests, which are then settled according to a set of simple rules. The model features the main elements of a real-life system, including a central bank acting as liquidity provider, and a simplified money market. A simulation exercise using synthetic data of BI-REL (the Italian RTGS) predicts the macroscopic impact of a disruptive event on the flow of interbank payments. In our reduced-scale system, three hypothetical distinct phases emerge after the disruptive event: 1) a liquidity sink effect is generated and the participants\' liquidity expectations turn out to be excessive; 2) an illusory thickening of the money market follows, along with increased payment delays; and, finally 3) defaulted obligations dramatically rise. The banks cannot staunch the losses accruing on defaults, even after they become fully aware of the critical event, and a scenario emerges in which it might be necessary for the central bank to step in as liquidity provider.

Tatiana Filatova, Dawn C. Parker and Anne van der Veen
Journal of Artificial Societies and Social Simulation 12 (1) 3

Kyeywords: Location Choice, Urban Land Market, Agent-Based Computational Economics, Land Use, Land Rent Gradient, Spatial Simulation
Abstract: We present a new bilateral agent-based land market model, which moves beyond previous work by explicitly modeling behavioral drivers of land-market transactions on both the buyer and seller side; formation of bid prices (of buyers) and ask prices (of sellers); and the relative division of the gains from trade from the market transactions. We analyze model output using a series of macro-scale economic and landscape pattern measures, including land rent gradients estimated using simple regression models. We first demonstrate that our model replicates relevant theoretical results of the traditional Alonso/Von Thünen model (structural validation). We then explore how urban morphology and land rents change as the relative market power of buyers and sellers changes (i.e., we move from a \'sellers\' market\' to a \'buyers\' market\'). We demonstrate that these strategic price dynamics have differential effects on land rents, but both lead to increased urban expansion.

Rob J. Nadolski, Bert van den Berg, Adriana J. Berlanga, Hendrik Drachsler, Hans G.K. Hummel, Rob E.J.R. Koper and Peter B. Sloep
Journal of Artificial Societies and Social Simulation 12 (1) 4

Kyeywords: Recommendation Strategy; Simulation Study; Way-Finding; Collaborative Filtering; Rating
Abstract: Recommender systems for e-learning demand specific pedagogy-oriented and hybrid recommendation strategies. Current systems are often based on time-consuming, top down information provisioning combined with intensive data-mining collaborative filtering approaches. However, such systems do not seem appropriate for Learning Networks where distributed information can often not be identified beforehand. Providing sound way-finding support for lifelong learners in Learning Networks requires dedicated personalised recommender systems (PRS), that offer the learners customised advise on which learning actions or programs to study next. Such systems should also be practically feasible and be developed with minimized effort. Currently, such so called light-weight PRS systems are scarcely available. This study shows that simulation studies can support the analysis and optimisation of PRS requirements prior to starting the costly process of their development, and practical implementation (including testing and revision) during field experiments in real-life learning situations. This simulation study confirms that providing recommendations leads towards more effective, more satisfied, and faster goal achievement. Furthermore, this study reveals that a light-weight hybrid PRS-system based on ratings is a good alternative for an ontology-based system, in particular for low-level goal achievement. Finally, it is found that rating-based light-weight hybrid PRS-systems enable more effective, more satisfied, and faster goal attainment than peer-based light-weight hybrid PRS-systems (incorporating collaborative techniques without rating).

Luis R. Izquierdo, Segismundo S. Izquierdo, José Manuel Galán and José Ignacio Santos
Journal of Artificial Societies and Social Simulation 12 (1) 6

Kyeywords: Computer Modelling, Simulation, Markov, Stochastic Processes, Analysis, Re-Implementation
Abstract: The aim of this paper is to assist researchers in understanding the dynamics of simulation models that have been implemented and can be run in a computer, i.e. computer models. To do that, we start by explaining (a) that computer models are just input-output functions, (b) that every computer model can be re-implemented in many different formalisms (in particular in most programming languages), leading to alternative representations of the same input-output relation, and (c) that many computer models in the social simulation literature can be usefully represented as time-homogeneous Markov chains. Then we argue that analysing a computer model as a Markov chain can make apparent many features of the model that were not so evident before conducting such analysis. To prove this point, we present the main concepts needed to conduct a formal analysis of any time-homogeneous Markov chain, and we illustrate the usefulness of these concepts by analysing 10 well-known models in the social simulation literature as Markov chains. These models are: • Schelling\'s (1971) model of spatial segregation • Epstein and Axtell\'s (1996) Sugarscape • Miller and Page\'s (2004) standing ovation model • Arthur\'s (1989) model of competing technologies • Axelrod\'s (1986) metanorms models • Takahashi\'s (2000) model of generalized exchange • Axelrod\'s (1997) model of dissemination of culture • Kinnaird\'s (1946) truels • Axelrod and Bennett\'s (1993) model of competing bimodal coalitions • Joyce et al.\'s (2006) model of conditional association In particular, we explain how to characterise the transient and the asymptotic dynamics of these computer models and, where appropriate, how to assess the stochastic stability of their absorbing states. In all cases, the analysis conducted using the theory of Markov chains has yielded useful insights about the dynamics of the computer model under study.

Chao Yang, Kurahashi Setsuya, Keiko Kurahashi, Isao Ono and Takao Terano
Journal of Artificial Societies and Social Simulation 12 (2) 5

Kyeywords: Agent-Based Simulation, Grid Oriented Genetic Algorithm, Inverse Simulation, Family Norm, Civil Service Examination
Abstract: In this paper, following our previous work on civil service examinations in imperial China, we investigate women's role in a Chinese historical family line using an agent-based simulation (ABS) model with a grid oriented genetic algorithm (GOGA) framework. We utilize a GOGA framework, because our ABS had such large parameter spaces with real values that it required much greater computational resources. First, we studied the genealogical records. Second, based on that study, we implemented an agent-based model with the family lines branched out into two clusters to compare different family norms. Third, using an "inverse simulation" technique, we optimized the agent-based model in order to fit the simulation profiles to real profile data with real-coded GA. From these intensive experiments, we have found that (1) The combined influence of the father, uncle, mother and the aunt has important significance in maintaining a successful family norm, and (2) a particular role of the aunt to pass it on as well.

Heiko Rauhut and Marcel Junker
Journal of Artificial Societies and Social Simulation 12 (3) 1

Kyeywords: Crime, Punishment, Control, Bounded Rationality, Agent-Based Simulation, Experiment, Game Theory
Abstract: Is it rational to reduce criminal activities if punishments are increased? While intuition might suggest so, game theory concludes differently. From the game theoretical perspective, inspectors anticipate the effect of increased punishments on criminal behavior and reduce their inspection activities accordingly. This implies that higher punishments reduce inspections and do not affect crime rates. We present two laboratory experiments, which challenge this perspective by demonstrating that both, criminals and inspectors, are affected by punishment levels. Thereupon, we investigate with agent-based simulations, whether models of bounded rationality can explain our empirical data. We differentiate between two kinds of bounded rationality; the first considers bounded learning from social interaction, the second bounded decision-making. Our results suggest that humans show both kinds of bounded rationality in the strategic situation of crime, control and punishment. We conclude that it is not the rationality but the bounded rationality in humans that makes punishment effective.

Whan-Seon Kim
Journal of Artificial Societies and Social Simulation 12 (3) 4

Kyeywords: Complex Adaptive System, Agent-Based Social Simulation, Supply Network, Trust
Abstract: This paper models a supply network as a complex adaptive system (CAS), in which firms or agents interact with one another and adapt themselves. And it applies agent-based social simulation (ABSS), a research method of simulating social systems under the CAS paradigm, to observe emergent outcomes. The main purposes of this paper are to consider a social factor, trust, in modeling the agents\' behavioral decision-makings and, through the simulation studies, to examine the intermediate self-organizing processes and the resulting macro-level system behaviors. The simulations results reveal symmetrical trust levels between two trading agents, based on which the degree of trust relationship in each pair of trading agents as well as the resulting collaboration patterns in the entire supply network emerge. Also, it is shown that agents\' decision-making behavior based on the trust relationship can contribute to the reduction in the variability of inventory levels. This result can be explained by the fact that mutual trust relationship based on the past experiences of trading diminishes an agent\'s uncertainties about the trustworthiness of its trading partners and thereby tends to stabilize its inventory levels.

Francesc S. Beltran, Salvador Herrando, Doris Ferreres, Marc-Antoni Adell, Violant Estreder and Marcos Ruiz-Soler
Journal of Artificial Societies and Social Simulation 12 (3) 5

Kyeywords: Cellular Automata, Computational Simulations, Language, Social Dynamics
Abstract: Language extinction as a consequence of language shifts is a widespread social phenomenon that affects several million people all over the world today. An important task for social sciences research should therefore be to gain an understanding of language shifts, especially as a way of forecasting the extinction or survival of threatened languages, i.e., determining whether or not the subordinate language will survive in communities with a dominant and a subordinate language. In general, modeling is usually a very difficult task in the social sciences, particularly when it comes to forecasting the values of variables. However, the cellular automata theory can help us overcome this traditional difficulty. The purpose of this article is to investigate language shifts in the speech behavior of individuals using the methodology of the cellular automata theory. The findings on the dynamics of social impacts in the field of social psychology and the empirical data from language surveys on the use of Catalan in Valencia allowed us to define a cellular automaton and carry out a set of simulations using that automaton. The simulation results highlighted the key factors in the progression or reversal of a language shift and the use of these factors allowed us to forecast the future of a threatened language in a bilingual community.

Diana Adamatti, Jaime Simão Sichman and Helder Coelho
Journal of Artificial Societies and Social Simulation 12 (3) 7

Kyeywords: Role-Playing Games, Multi-Agent Based Simulation, Natural Resources, Virtual Players
Abstract: The GMABS (Games and Multi-Agent-Based Simulation) methodology was created from the integration of RPG and MABS techniques. This methodology links the dynamic capacity of MABS (Multi-Agent-Based Simulation) and the discussion and learning capacity of RPG (Role-Playing Games). Using GMABS, we have developed two prototypes in the natural resources management domain. The first prototype, called JogoMan (Adamatti et. al, 2005), is a paper-based game: all players need to be physically present in the same place and time, and there is a minimum needed number of participants to play the game. In order to avoid this constraint, we have built a second prototype, called ViP-JogoMan (Adamatti et. al, 2007), which is an extension of the first one. This second game enables the insertion of virtual players that can substitute some real players in the game. These virtual players can partially mime real behaviors and capture autonomy, social abilities, reaction and adaptation of the real players. We have chosen the BDI architecture to model these virtual players, since its paradigm is based on folk psychology; hence, its core concepts easily map the language that people use to describe their reasoning and actions in everyday life. ViP-JogoMan is a computer-based game, in which people play via Web, players can be in different places and it does not have a hard constraint regarding the minimum number of real players. Our aim in this paper is to present some test results obtained with both prototypes, as well as to present a preliminary discussion on how the insertion of virtual players has affected the game results.

Oliver Will
Journal of Artificial Societies and Social Simulation 12 (4) 11

Kyeywords: Replication, Social Dilemma Situations, Trust, Simulation Methodology, Cooperation
Abstract: The paper at hand aimes at identifying the assumptions that lead to the results presented in an article by Michael Macy and Yoshimichi Sato published in PNAS. In answer to a failed replication, the authors provided the source code of their model and here the results of carefully studying that code are presented. The main finding is that the simulation program implements an assumption that is most probably an unwilling, unintended, and unwanted implication of the code. This implied assumption is never mentioned in Macy and Sato's article and if the authors wanted to program what they describe in their article then it is due to a programming error. After introducing the reader to the discussion, data that stem from a new replication based on the assumptions extracted from the source code is compared with the results published in Macy and Sato's original article. The replicated results are sufficiently similar to serve as a strong indicator that this new replication implements the same relevant assumptions as the original model. Afterwards it is shown that a removal of the dubious assumption leads to results that are dramatically different from those published in Macy and Sato's PNAS article.

Matthias Meyer, Iris Lorscheid and Klaus G. Troitzsch
Journal of Artificial Societies and Social Simulation 12 (4) 12

Kyeywords: Citation Analysis, Co-Citation Analysis, Lines of Research, Multidisciplinary, Science Studies, Social Simulation
Abstract: Social simulation is often described as a multidisciplinary and fast-moving field. This can make it difficult to obtain an overview of the field both for contributing researchers and for outsiders who are interested in social simulation. The Journal for Artificial Societies and Social Simulation (JASSS) completing its tenth year provides a good opportunity to take stock of what happened over this time period. First, we use citation analysis to identify the most influential publications and to verify characteristics of social simulation such as its multidisciplinary nature. Then, we perform a co-citation analysis to visualize the intellectual structure of social simulation and its development. Overall, the analysis shows social simulation both in its early stage and during its first steps towards becoming a more differentiated discipline.

Thomas Brenner and Claudia Werker
Journal of Artificial Societies and Social Simulation 12 (4) 2

Kyeywords: Policy Advice, Simulation Models, Uncertainty, Methodology
Abstract: When advising policy we face the fundamental problem that economic processes are uncertain. Consequently, policy can err. In this paper we show how the use of simulation models can reduce policy errors by inferring empirically reliable and meaningful statements about economic processes. We suggest that policy is best based on so-called abductive simulation models, which help to better understand how policy measures can influence economic processes. We show that abductive simulation models use a combination of theoretical and empirical analysis based on different data sets. By way of example we show what policy can learn with the help of abductive simulation models, namely how policy measures can influence the emergence of a regional cluster.

Gönenç Yücel and Els van Daalen
Journal of Artificial Societies and Social Simulation 12 (4) 3

Kyeywords: Simulation, Validation, Model Assessment, Policy Analysis, Model Typology
Abstract: Simulation models, being in use for a long time in natural sciences and engineering domains, are diffusing to a wider context including policy analysis studies. The differences between the nature of the domain of application, as well as the increased variety of usage partially induced by this difference naturally imply new challenges to be overcome. One of these challenges is related to the assessment of the simulation-based outcomes in terms of their reliability and relevance in the policy context being studied. The importance of this assessment is twofold. First of all, it is all about conducting a high quality policy study with effective results. However, the quality of the study does not necessarily imply acceptance of the results by the clients and/or colleagues. This problem of policy analysts increases the importance of such an assessment; an effective assessment may induce the acceptance of the conclusions drawn from the study by the clients and/or colleagues. The main objective of this paper is to introduce an objective-based assessment perspective for simulation model-supported policy studies. As a first step towards such a goal, an objective-based classification of models is introduced. Based on that, we will discuss the importance of different aspects of the assessment for each type. In doing so, we aim to provide a structured discussion that may serve as a sort of methodological guideline to be used by policy analysts, and also by clients.

Stefania Bandini, Sara Manzoni and Giuseppe Vizzari
Journal of Artificial Societies and Social Simulation 12 (4) 4

Kyeywords: Multi-Agent Systems, Agent-Based Modeling and Simulation
Abstract: The term computer simulation is related to the usage of a computational model in order to improve the understanding of a system's behavior and/or to evaluate strategies for its operation, in explanatory or predictive schemes. There are cases in which practical or ethical reasons make it impossible to realize direct observations: in these cases, the possibility of realizing 'in-machina' experiments may represent the only way to study, analyze and evaluate models of those realities. Different situations and systems are characterized by the presence of autonomous entities whose local behaviors (actions and interactions) determine the evolution of the overall system; agent-based models are particularly suited to support the definition of models of such systems, but also to support the design and implementation of simulators. Agent-Based models and Multi-Agent Systems (MAS) have been adopted to simulate very different kinds of complex systems, from the simulation of socio-economic systems to the elaboration of scenarios for logistics optimization, from biological systems to urban planning. This paper discusses the specific aspects of this approach to modeling and simulation from the perspective of Informatics, describing the typical elements of an agent-based simulation model and the relevant research.

Tetsushi Ohdaira and Takao Terano
Journal of Artificial Societies and Social Simulation 12 (4) 7

Kyeywords: Cooperation, Altruism, Agent-Based Simulation, Evolutionary Game Theory
Abstract: In the research addressing the prisoner's dilemma game, the effectiveness and accountableness of the method allowing for the emergence of cooperation is generally discussed. The most well-known solutions for this question are memory based iteration, the tag used to distinguish between defector and cooperator, the spatial structure of the game and the either direct or indirect reciprocity. We have also challenged to approach the topic from a different point of view namely that temperate acquisitiveness in decision making could be possible to achieve cooperation. It was already shown in our previous research that the exclusion of the best decision had a remarkable effect on the emergence of an almost cooperative state. In this paper, we advance the decision of our former research to become more explainable by introducing the second-best decision. If that decision is adopted, players also reach an extremely high level cooperative state in the prisoner's dilemma game and also in that of extended strategy expression. The cooperation of this extended game is facilitated only if the product of two parameters is under the criticality. In addition, the applicability of our model to the problem in the real world is discussed.

Brian Heath, Raymond Hill and Frank Ciarallo
Journal of Artificial Societies and Social Simulation 12 (4) 9

Kyeywords: Agent-Based Modeling, Survey, Current Practices, Simulation Validation, Simulation Purpose
Abstract: In the 1990s, Agent-Based Modeling (ABM) began gaining popularity and represents a departure from the more classical simulation approaches. This departure, its recent development and its increasing application by non-traditional simulation disciplines indicates the need to continuously assess the current state of ABM and identify opportunities for improvement. To begin to satisfy this need, we surveyed and collected data from 279 articles from 92 unique publication outlets in which the authors had constructed and analyzed an agent-based model. From this large data set we establish the current practice of ABM in terms of year of publication, field of study, simulation software used, purpose of the simulation, acceptable validation criteria, validation techniques and complete description of the simulation. Based on the current practice we discuss six improvements needed to advance ABM as an analysis tool. These improvements include the development of ABM specific tools that are independent of software, the development of ABM as an independent discipline with a common language that extends across domains, the establishment of expectations for ABM that match their intended purposes, the requirement of complete descriptions of the simulation so others can independently replicate the results, the requirement that all models be completely validated and the development and application of statistical and non-statistical validation techniques specifically for ABM.

Seppo Sallila
Journal of Artificial Societies and Social Simulation 13 (1) 1

Kyeywords: Inequality, Optimization, Poverty, Public Policy, Simulation Methodology, Tax-Benefit System
Abstract: In this study, a static microsimulation model SOMA is used to optimize Finland's tax-benefit legislation to alleviate poverty or at least to reduce it significantly. The method is a classical optimization method using a greed optimization strategy. This means an iterative process, where only one poverty diminishing parameter is changed by 10% from its earlier value at each iteration. Expenses are also optimized to reduce inequality as measured by the Gini-coefficient. Revenues and expenses are balanced at every iteration. Certain parameters of social assistance were found to be the most effective in reducing poverty. However by raising substantially the basic unemployment benefit, basic pensions, housing benefits and study grants - leaving social assistance untouched - poverty was reduced by under 50 percent. This means that social assistance is still required to reduce poverty further. Costs are most effectively financed by raising capital income tax.

Stuart Rossiter, Jason Noble and Keith R.W. Bell
Journal of Artificial Societies and Social Simulation 13 (1) 10

Kyeywords: Social Simulation, Methodology, Epistemology, Ideology, Validation
Abstract: Because of features that appear to be inherent in many social systems, modellers face complicated and subjective choices in positioning the scientific contribution of their research. This leads to a diversity of approaches and terminology, making interdisciplinary assessment of models highly problematic. Such modellers ideally need some kind of accessible, interdisciplinary framework to better understand and assess these choices. Existing texts tend either to take a specialised metaphysical approach, or focus on more pragmatic aspects such as the simulation process or descriptive protocols for how to present such research. Without a sufficiently neutral treatment of why a particular set of methods and style of model might be chosen, these choices can become entwined with the ideological and terminological baggage of a particular discipline. This paper attempts to provide such a framework. We begin with an epistemological model, which gives a standardised view on the types of validation available to the modeller, and their impact on scientific value. This is followed by a methodological framework, presented as a taxonomy of the key dimensions over which approaches are ultimately divided. Rather than working top-down from philosophical principles, we characterise the issues as a practitioner would see them. We believe that such a characterisation can be done 'well enough', where 'well enough' represents a common frame of reference for all modellers, which nevertheless respects the essence of the debate's subtleties and can be accepted as such by a majority of 'methodologists'. We conclude by discussing the limitations of such an approach, and potential further work for such a framework to be absorbed into existing, descriptive protocols and general social simulation texts.

Franciszek Rakowski, Magdalena Gruziel, Michal Krych and Jan P Radomski
Journal of Artificial Societies and Social Simulation 13 (1) 13

Kyeywords: Agent Based Model, Educational Availability, Daily Commuting, Social Network, Virtual Society Simulations
Abstract: In this study we describe a simulation platform used to create a virtual society of Poland, with a particular emphasis on contact patterns arising from daily commuting to schools or workplaces. In order to reproduce the map of contacts, we are using a geo-referenced Agent Based Model. Within this framework, we propose a set of different stochastic algorithms, utilizing available aggregated census data. Based on this model system, we present selected statistical analysis, such as the accessibility of schools or the location of rescue service units. This platform will serve as a base for further large scale epidemiological and transportation simulation studies. However, the first approach to a simple, country-wide transportation model is also presented here. The application scope of the platform extends beyond the simulations of epidemic or transportation, and pertains to any situation where there are no easily available means, other than computer simulations, to conduct large scale investigations of complex population dynamics.

Pierre Livet, Jean-Pierre Muller, Denis Phan and Lena Sanders
Journal of Artificial Societies and Social Simulation 13 (1) 3

Kyeywords: Ontology, Agent-Based Computational Economic, Agent-Based Model of Simulation, Model Design, Model Building, Knowledge Framework, Spatial Simulation, Social Simulation, Ontological Test
Abstract: Agent-Based Models are useful to describe and understand social, economic and spatial systems\' dynamics. But, beside the facilities which this methodology offers, evaluation and comparison of simulation models are sometimes problematic. A rigorous conceptual frame needs to be developed. This is in order to ensure the coherence in the chain linking at the one extreme the scientist\'s hypotheses about the modeled phenomenon and at the other the structure of rules in the computer program. This also systematizes the model design from the thematician conceptual framework as well. The aim is to reflect upon the role that a well defined ontology, based on the crossing of the philosophical and the computer science insights, can play to solve such questions and help the model building. We analyze different conceptions of ontology, introduce the \'ontological test\' and show its usefulness to compare models. Then we focus on the model building and show the place of a systematic ABM ontology. The latter process is situated within a larger framework called the \'knowledge framework\' in which not only the ontologies but also the notions of theory, model and empirical data take place. At last the relation between emergence and ontology is discussed.

Denis Phan and Franck Varenne
Journal of Artificial Societies and Social Simulation 13 (1) 5

Kyeywords: Agent-Based Models and Simulations, Epistemology, Economics, Social Sciences, Conceptual Exploration, Model World, Credible World, Experiment, Denotational Hierarchy
Abstract: Now that complex Agent-Based Models and computer simulations spread over economics and social sciences - as in most sciences of complex systems -, epistemological puzzles (re)emerge. We introduce new epistemological concepts so as to show to what extent authors are right when they focus on some empirical, instrumental or conceptual significance of their model or simulation. By distinguishing between models and simulations, between types of models, between types of computer simulations and between types of empiricity obtained through a simulation, section 2 gives the possibility to understand more precisely - and then to justify - the diversity of the epistemological positions presented in section 1. Our final claim is that careful attention to the multiplicity of the denotational powers of symbols at stake in complex models and computer simulations is necessary to determine, in each case, their proper epistemic status and credibility.

Claudio Cioffi-Revilla
Journal of Artificial Societies and Social Simulation 13 (1) 7

Kyeywords: Agent-Based Modeling Methodology, M2M, Social Simulation, Computational Social Science, Social Complexity, Inner Asia
Abstract: Social simulation - an emerging field of computational social science - has progressed from simple toy models to increasingly realistic models of complex social systems, such as agent-based models where heterogeneous agents interact with changing natural or artificial environments. These larger, multidisciplinary projects require a scientific research methodology distinct from, say, simpler social simulations with more limited scope, intentionally minimal complexity, and typically under a single investigator. This paper proposes a methodology for complex social simulations - particularly inter- and multi-disciplinary socio-natural systems with multi-level architecture - based on a succession of models akin to but distinct from the late Imre Lakatos' notion of a 'research programme'. The proposed methodology is illustrated through examples from the Mason-Smithsonian project on agent-based models of the rise and fall of polities in Inner Asia. While the proposed methodology requires further development, so far it has proven valuable for advancing the scientific objectives of the project and avoiding some pitfalls.

Alan Baker
Journal of Artificial Societies and Social Simulation 13 (1) 9

Kyeywords: Emergence, Simulation, Explanation
Abstract: One approach to characterizing the elusive notion of emergence is to define that a property is emergent if and only if its presence can be derived but only by simulation. In this paper I investigate the pros and cons of this approach, focusing in particular on whether an appropriately distinct boundary can be drawn between simulation-based and non-simulation-based methods. I also examine the implications of this definition for the epistemological role of emergent properties in prediction and in explanation.

Tibor Bosse and Charlotte Gerritsen
Journal of Artificial Societies and Social Simulation 13 (2) 5

Kyeywords: Agent-Based Modelling, Criminal Hot Spots, Displacement, Reputation, Social Simulation, Analysis
Abstract: Within the field of Criminology, the spatio-temporal dynamics of crime are an important subject of study. In this area, typical questions are how the behaviour of offenders, targets, and guardians can be explained and predicted, as well as the emergence and displacement of criminal hot spots. In this article we present a combination of software tools that can be used as an experimental environment to address such questions. In particular, these tools comprise an agent-based simulation model, a verification tool, and a visualisation tool. The agent-based simulation model specifically focuses on the interplay between hot spots and reputation. Using this environment, a large number of simulation runs have been performed, of which results have been formally analysed. Based on these results, we argue that the presented environment offers a valuable approach to analyse the dynamics of criminal hot spots.

Stefan König, Sebastian Hudert and Torsten Eymann
Journal of Artificial Societies and Social Simulation 13 (2) 6

Kyeywords: Multi-Agent Simulation, Internet, Simulation Tools
Abstract: Visions of 21st century information systems show highly specialized digital services and resources, which interact continuously and with a global reach. Especially with the emergence of technologies, such as the semantic web or software agents, intelligent services within these settings can be implemented, automatically communicating and negotiating over the Internet about digital resources without human intervention. Such environments will eventually realize the vision of an open and global Internet of Services (IoS). In this paper we present an agent-based simulation model and toolkit for the IoS: 'SimIS - Simulating an Internet of Services'. Employing SimIS, distributed management mechanisms and protocols can be investigated in a simulated IoS environment before their actual deployment.

Vicenç Quera, Francesc S. Beltran and Ruth Dolado
Journal of Artificial Societies and Social Simulation 13 (2) 8

Kyeywords: Flocking Behaviour; Hierarchical Leadership; Agent-Based Simulation; Social Dynamics
Abstract: We have studied how leaders emerge in a group as a consequence of interactions among its members. We propose that leaders can emerge as a consequence of a self-organized process based on local rules of dyadic interactions among individuals. Flocks are an example of self-organized behaviour in a group and properties similar to those observed in flocks might also explain some of the dynamics and organization of human groups. We developed an agent-based model that generated flocks in a virtual world and implemented it in a multi-agent simulation computer program that computed indices at each time step of the simulation to quantify the degree to which a group moved in a coordinated way (index of flocking behaviour) and the degree to which specific individuals led the group (index of hierarchical leadership). We ran several series of simulations in order to test our model and determine how these indices behaved under specific agent and world conditions. We identified the agent, world property, and model parameters that made stable, compact flocks emerge, and explored possible environmental properties that predicted the probability of becoming a leader.

Adam Zagorecki, Kilkon Ko and Louise K. Comfort
Journal of Artificial Societies and Social Simulation 13 (3) 3

Kyeywords: Agent-Based Simulation, Emergency Management, Network Evolution, Performance
Abstract: Achieving efficiency in coordinated action in rapidly changing environments has challenged both researchers and practitioners. Emergency events require both rapid response and effective coordination among participating organizations. We created a simulated operations environment using agent-based modeling to test the efficiency of six different organizational designs that varied the exercise of authority, degree of uncertainty, and access to information. Efficiency is measured in terms of response time, identifying time as the most valuable resource in emergency response. Our findings show that, contrary to dominant organizational patterns of hierarchical authority that limit communication among members via strict reporting rules, any communication among members increases the efficiency of organizations operating in uncertain environments. We further found that a smaller component of highly interconnected, self adapting agents emerges over time to support the organization\'s adaptation in changing conditions. In uncertain environments, heterogeneous agents prove more efficient in sharing information that guides coordination than homogeneous agents.

Roy Wilson
Journal of Artificial Societies and Social Simulation 13 (3) 8

Kyeywords: Agent-Based Social Simulation, Weak Emergence, Social Networks, Kolmogorov Complexity, Upward Causation, Downward Causation
Abstract: This paper interprets a particular agent-based social simulation (ABSS) in terms of the third way of understanding agent-based simulation proposed by Conte. It is proposed that the normalized compression distance (derived from estimates of Kolmogorov complexity) between the initial and final macrolevel states of the ABSS provides a quantitative measure of the degree to which the results obtained via the ABSS might be obtained via a closed-form expression. If the final macrolevel state of an ABSS can only be obtained by simulation, this confers on agent-based social simulations a special status. Future empirical (computational) work and epistemological analyses are proposed.

Tony Bastin Roy Savarimuthu, Stephen Cranefield, Maryam A. Purvis and Martin K. Purvis
Journal of Artificial Societies and Social Simulation 13 (4) 3

Kyeywords: Norms, Social Norms, Obligations, Norm Identification, Agent-Based Simulation, Simulation of Norms, Artificial Societies, Normative Multi-Agent Systems (NorMAS)
Abstract: Most works on norms have investigated how norms are regulated using institutional mechanisms. Very few works have focused on how an agent may infer the norms of a society without the norm being explicitly given to the agent. This paper describes a mechanism for identifying one type of norm, an obligation norm. The Obligation Norm Inference (ONI) algorithm described in this paper makes use of an association rule mining approach to identify obligation norms. Using agent based simulation of a virtual restaurant we demonstrate how an agent can identify the tipping norm. The experiments that we have conducted demonstrate that an agent in the system is able to add, remove and modify norms dynamically. An agent can also flexibly modify the parameters of the system based on whether it is successful in identifying a norm.

Shah Jamal Alam, Armando Geller, Ruth Meyer and Bogdan Werth
Journal of Artificial Societies and Social Simulation 13 (4) 6

Kyeywords: Cognition, Contextualized Reasoning, Evidence-Driven Agent-Based Social Simulation, Empirical Agent-Based Social Simulation, Rich Cognitive Modelling, Tzintzuntzan
Abstract: In many computational social simulation models only cursory reference to the foundations of the agent cognition used is made and computational expenses let many modellers chose simplistic agent cognition architectures. Both choices run counter to expectations framed by scholars active in the domain of rich cognitive modelling that see agent reasoning as socially inherently contextualized. The Manchester school of social simulation proposed a particular kind of a socially contextualized reasoning mechanism, so called endorsements, to implement the cognitive processes underlying agent action selection that eventually causes agent interaction. Its usefulness lies in its lightweight architecture and in taking into account folk psychological conceptions of how reasoning works. These and other advantages make endorsements an amenable tool in everyday social simulation modelling. A yet outstanding comprehensive introduction to the concept of endorsements is provided and its theoretical basis is extended and extant research is critically reviewed. Improvements to endorsements regarding memory and perception are suggested and tested against a case-study.

Gijs de Bakker, Jan van Bruggen, Wim Jochems and Peter B. Sloep
Journal of Artificial Societies and Social Simulation 14 (1) 1

Kyeywords: Peer Support, Peer Allocation, Computational Simulations, System Dynamics, Distance Learning
Abstract: While student populations in higher education are becoming more heterogeneous, recently several attempts have been made to introduce online peer support to decrease the tutor load of teachers. We propose a system that facilitates synchronous online reciprocal peer support activities for ad hoc student questions: the Synchronous Allocated Peer Support (SAPS) system. Via this system, students with questions during their learning are allocated to competent fellow-students for answering. The system is designed for reciprocal peer support activities among a group of students who are working on the same fixed modular material every student has to finish, such as courses with separate chapters. As part of a requirement analysis of online reciprocal peer support to succeed, this chapter is focused on the second requirement of peer competence and sustainability of our system. Therefore a study was conducted with a simulation of a SAPS-based allocation mechanism in the NetLogo simulation environment and focuses on the required minimum population size, the effect of the addition of extra allocation parameters or disabling others on the mechanism\'s effectiveness, and peer tutor load spread in various conditions and its influence on the mechanism\'s effectiveness. The simulation shows that our allocation mechanism should be able to facilitate online peer support activities among groups of students. The allocation mechanism holds over time and a sufficient number of students are willing and competent to answer fellow-students\' questions. Also, fine-tuning the parameters (e.g. extra selection criteria) of the allocation mechanism further enhances its effectiveness.

Krzysztof Malarz, Piotr Gronek and Krzysztof Kulakowski
Journal of Artificial Societies and Social Simulation 14 (1) 2

Kyeywords: Mass Opinion; Computer Simulations; Social Networks;
Abstract: Recent formulation of the Zaller model of mass opinion is generalized to include the interaction between agents. The mechanism of interaction is close to the bounded confidence model. The outcome of the simulation is the probability distribution of opinions on a given issue as dependent on the mental capacity of agents. Former result was that a small capacity leads to a strong belief. Here we show that an intensive interaction between agents also leads to a consensus, accepted without doubts.

Adam Wierzbicki and Radoslaw Nielek
Journal of Artificial Societies and Social Simulation 14 (1) 3

Kyeywords: Trust, Simulation, Fairness, Equity, Emergence, Reputation System
Abstract: Reputation systems have been used to support users in making decisions under uncertainty or risk that is due to the autonomous behavior of others. Research results support the conclusion that reputation systems can protect against exploitation by unfair users, and that they have an impact on the prices and income of users. This observation leads to another question: can reputation systems be used to assure or increase the fairness of resource distribution? This question has a high relevance in social situations where, due to the absence of established authorities or institutions, agents need to rely on mutual trust relations in order to increase fairness of distribution. This question can be formulated as a hypothesis: in reputation (or trust management) systems, fairness should be an emergent property. The notion of fairness can be precisely defined and investigated based on the theory of equity. In this paper, we investigate the Fairness Emergence hypothesis in reputation systems and prove that , under certain conditions, the hypothesis is valid for open and closed systems, even in unstable system states and in the presence of adversaries. Moreover, we investigate the sensitivity of Fairness Emergence and show that an improvement of the reputation system strengthens the emergence of fairness. Our results are confirmed using a trace-driven simulation from a large Internet auction site.

Ian Lustick
Journal of Artificial Societies and Social Simulation 14 (1) 7

Kyeywords: Secession, Virtualization, Pakistan, Simulation, Punjab, Rare Events
Abstract: In world politics the most important events are often rare events. Secession is a rare and important event. Secession of the center; when the dominant region of a country abandons its peripheries, is even rarer. But as the transformation of the Soviet Union into Russia and a collection of independent states demonstrates, it is an important kind of development. In this paper we illustrate the ambitious use of an agent-based virtualization model of Pakistan. By producing a large number of futures of the country, modeled according to best available data and theory, secession of the center--the emergence of Punjabistan--is shown to be rare although possible. Analysis of the trajectories leading toward that outcome suggests how it could come about; or be prevented.

Peer-Olaf Siebers and Uwe Aickelin
Journal of Artificial Societies and Social Simulation 14 (2) 2

Kyeywords: Retail Performance, Management Practices, Proactive Behaviour, Service Experience, Agent-Based Modelling, Simulation
Abstract: There has been a noticeable shift in the relative composition of the industry in the developed countries in recent years; manufacturing is decreasing while the service sector is becoming more important. However, currently most simulation models for investigating service systems are still built in the same way as manufacturing simulation models, using a process-oriented world view, i.e. they model the flow of passive entities through a system. These kinds of models allow studying aspects of operational management but are not well suited for studying the dynamics that appear in service systems due to human behaviour. For these kinds of studies we require tools that allow modelling the system and entities using an object-oriented world view, where intelligent objects serve as abstract \'actors\' that are goal directed and can behave proactively. In our work we combine process-oriented discrete event simulation modelling and object-oriented agent based simulation modelling to investigate the impact of people management practices on retail productivity. In this paper, we reveal in a series of experiments what impact considering proactivity can have on the output accuracy of simulation models of human centric systems. The model and data we use for this investigation are based on a case study in a UK department store. We show that considering proactivity positively influences the validity of these kinds of models and therefore allows analysts to make better recommendations regarding strategies to apply people management practices.

Christopher D. Hollander and Annie S. Wu
Journal of Artificial Societies and Social Simulation 14 (2) 6

Kyeywords: Norms, Normative Agents, Agents, Agent-Based System, Agent-Based Simulation, Agent-Based Modeling
Abstract: Recent years have seen an increase in the application of ideas from the social sciences to computational systems. Nowhere has this been more pronounced than in the domain of multiagent systems. Because multiagent systems are composed of multiple individual agents interacting with each other many parallels can be drawn to human and animal societies. One of the main challenges currently faced in multiagent systems research is that of social control. In particular, how can open multiagent systems be configured and organized given their constantly changing structure? One leading solution is to employ the use of social norms. In human societies, social norms are essential to regulation, coordination, and cooperation. The current trend of thinking is that these same principles can be applied to agent societies, of which multiagent systems are one type. In this article, we provide an introduction to and present a holistic viewpoint of the state of normative computing (computational solutions that employ ideas based on social norms.) To accomplish this, we (1) introduce social norms and their application to agent-based systems; (2) identify and describe a normative process abstracted from the existing research; and (3) discuss future directions for research in normative multiagent computing. The intent of this paper is to introduce new researchers to the ideas that underlie normative computing and survey the existing state of the art, as well as provide direction for future research.

Tetsushi Ohdaira and Takao Terano
Journal of Artificial Societies and Social Simulation 14 (3) 3

Kyeywords: Cooperation, Second-Best Decision, Multi-Agent Simulation, Spatial Game, Collusive Tendering
Abstract: Recently, the area of study of spatial game continuously has extended, and researchers have especially presented a lot of works of coevolutionary mechanism. We have recognized coevolutionary mechanism as one of the factors for the promotion of cooperation like five rules by Nowak. However, those studies still deal with the optimal response (best decision). The best decision is persuasive in most cases, but does not apply to all situations in the real world. Contemplating that question, researchers have presented some works discussing not only the best decision but also the second-best decision. Those studies compare the results between the best and the second-best, and also state the applicability of the second-best decision. This study, considering that trend, has extended the match between two groups to spatial game with the second-best decision. This extended model expresses relationships of groups as a spatial network, and every group matches other groups of relationships. Then, we examine how mutual cooperation changes in each case where either we add probabilistic perturbation to relationships or ties form various types of the structure. As a result, unlike most results utilizing the best decision, probabilistic perturbation does not induce any change. On the other hand, when ties are the scale-free structure, mutual cooperation is enhanced like the case of the best decision. When we probe the evolution of strategies in that case, groups with many ties play a role for leading the direction of decision as a whole. This role appears without explicit assignment. In the discussion, we also state that the presented model has an analogy to the real situation, collusive tendering.

Isamu Okada
Journal of Artificial Societies and Social Simulation 14 (3) 4

Kyeywords: Corporate Social Responsibility, Agent-Based Simulation, Sustainability, Multiple Sector Model, Micro Economy
Abstract: An agent-based model of firms and their stakeholders' economic actions was used to test the theoretical feasibility of sustainable corporate social responsibility activities. Corporate social responsibility has become important to many firms, but CSR activities tend to get less attention during busts than during boom times. The hypothesis tested is that the CSR activities of a firm are more economically rational if the economic actions of its stakeholders reflect the firm's level of CSR. Our model focuses on three types of stakeholders: workers, consumers, and shareholders. First, we construct a uniform framework based on a microeconomic foundation that includes these stakeholders and the corresponding firms. Then, we formulate parameters for CSR in this framework. Our aim is to identify the conditions under which every type of stakeholder derives benefits from a firm's CSR activities. We simulated our model with heterogeneous agents by computer using several scenarios. For each one, the simulation was run 100 times with different random seeds. We first simulated the homogeneous version discussed above to verify the concept of our model. Next, we simulated the case in which workers had heterogeneous abilities, the firms had cost for CSR activities, and the workers, consumers, and shareholders had zero CSR awareness. We tested the robustness of our simulation results by using sensitivity analysis. Specifically, we investigated the conditions for the pecuniary advantage of CSR activities and effects offsetting benefits of CSR activities. Finally, we developed a new model installed bounded rational and simulated. The results show that the economic actions of stakeholders during boom periods greatly affect the sustainability of CSR activities during slow periods. This insight should lead to a feasible and effective prescription for sustainable CSR activities.

Stephen Younger
Journal of Artificial Societies and Social Simulation 14 (3) 8

Kyeywords: Multi-Agent Simulation, Leadership, Violence, Warfare, Pacific Island Societies
Abstract: Multi-agent simulation was used to study the effect of simple models of leadership on interpersonal violence and warfare in small societies. Agents occupied a two dimensional landscape containing villages and food sources. Sharing and stealing contributed to normative reputation. Violence occurred during theft, in revenge killings, and in leader-directed warfare between groups. The simulations were run over many generations to examine the effect of violence on social development. The results indicate that leadership reduced the survival probability of the population. Interpersonal violence killed more agents than warfare when intra-group violence was permitted. More aggressive leaders did not always prevail over less aggressive leaders due to the inherent risks associated with attacks. The results of the simulation are compared to cross-cultural studies and to observations of indigenous Pacific island societies.

Wolfgang Balzer and Klaus Manhart
Journal of Artificial Societies and Social Simulation 14 (4) 11

Kyeywords: Social Simulation, Process, Science, Theory, Social Science, Philosophy of Science
Abstract: We lay open a position concerning the difference between scientific processes and processes in science. Not all processes in science are scientific. This leads into the center of social simulation. More scientific theories should be incorporated in social simulations, and this should lead to more united structural approaches.

Olivier Barreteau and Christophe Le Page
Journal of Artificial Societies and Social Simulation 14 (4) 12

Kyeywords: Participatory Research, Institutional Analysis and Design, Knowledge Flow, Agent Based Simulation
Abstract: This position paper contributes to the debate on perspectives for simulating the social processes of science through the specific angle of participatory research. This new way of producing science is still in its infancy and needs some step back and analysis, to understand what is taking place on the boundaries between academic, policy and lay worlds. We argue that social simulation of this practice of cooperation can help in understanding further this new way of doing science, building on existing experience in simulation of knowledge flows as well as pragmatic approaches in social sciences.

Bruce Edmonds, Nigel Gilbert, Petra Ahrweiler and Andrea Scharnhorst
Journal of Artificial Societies and Social Simulation 14 (4) 14

Kyeywords: Simulation, Science, Science and Technology Studies, Philosophy, Sociology, Social Processes
Abstract: Science is the result of a substantially social process. That is, science relies on many inter-personal processes, including: selection and communication of research findings, discussion of method, checking and judgement of others' research, development of norms of scientific behaviour, organisation of the application of specialist skills/tools, and the organisation of each field (e.g. allocation of funding). An isolated individual, however clever and well resourced, would not produce science as we know it today. Furthermore, science is full of the social phenomena that are observed elsewhere: fashions, concern with status and reputation, group-identification, collective judgements, social norms, competitive and defensive actions, to name a few. Science is centrally important to most societies in the world, not only in technical, military and economic ways, but also in the cultural impacts it has, providing ways of thinking about ourselves, our society and our environment. If we believe the following: simulation is a useful tool for understanding social phenomena, science is substantially a social phenomenon, and it is important to understand how science operates, then it follows that we should be attempting to build simulation models of the social aspects of science. This Special Section of <i>JASSS</i> presents a collection of position papers by philosophers, sociologists and others describing the features and issues the authors would like to see in social simulations of the many processes and aspects that we lump together as "science". It is intended that this collection will inform and motivate substantial simulation work as described in the last section of this introduction.

Kevin Zollman
Journal of Artificial Societies and Social Simulation 14 (4) 15

Kyeywords: Philosophy of Science, Sociology of Science, Computer Simulation
Abstract: While the popular image of scientists portrays them as objective, dispassionate observers of nature, actual scientists rarely are. It is not really known to what extent these individual departures from the scientific ideal effects the reliability of the scientific community. This paper suggests a number of concrete projects which help to determine this relationship.

Juan-Luis Suárez and Fernando Sancho
Journal of Artificial Societies and Social Simulation 14 (4) 19

Kyeywords: Cultural Dynamics, Cultural Complexity, Multi-Agent Based Simulation, Netlogo, Virtual Laboratory
Abstract: This article presents a Virtual Laboratory that enables the researcher to try hypothesis and confirm data analysis about different historical processes and cultural dynamics. This Virtual Cultural Laboratory (VCL) is developed using agent-based modeling technology. Individuals' tendencies and preferences as well as the behavior of cultural objects in the transformation of cultural information are taken into consideration. In addition, the effect of local interactions at different scales over time and space is visualized through the VCL interface. Information repositories, cultural items, borders, population size, individual' tendencies and other features are determined by the user. Finally, the researcher can also isolate specific factors whose effect on the global system might be of interest to the researcher. All the code can be found at http://projects.cultureplex.ca/

Flaminio Squazzoni and Károly Takács
Journal of Artificial Societies and Social Simulation 14 (4) 3

Kyeywords: Peer Review, Social Simulation, Social Norms, Selection Biases, Science Policy
Abstract: This article suggests to view peer review as a social interaction problem and shows reasons for social simulators to investigate it. Although essential for science, peer review is largely understudied and current attempts to reform it are not supported by scientific evidence. We suggest that there is room for social simulation to fill this gap by spotlighting social mechanisms behind peer review at the microscope and understanding their implications for the science system. In particular, social simulation could help to understand why voluntary peer review works at all, explore the relevance of social sanctions and reputational motives to increase the commitment of agents involved, cast light on the economic cost of this institution for the science system and understand the influence of signals and social networks in determining biases in the reviewing process. Finally, social simulation could help to test policy scenarios to maximise the efficacy and efficiency of various peer review schemes under specific circumstances and for everyone involved.

Marc Mölders, Robin D. Fink and Johannes Weyer
Journal of Artificial Societies and Social Simulation 14 (4) 6

Kyeywords: Systems Theory, Theory of Action and Decision Making, Academic Publication System, Science System, New Public Management, Agent-Based Modeling and Simulation
Abstract: The paper at hand applies agent-based modeling and simulations (ABMS) as a tool to reconstruct and to analyze how the science system works. A Luhmannian systems perspective is combined with a model of decision making of individual actors. Additionally, changes in the socio-political context of science, such as the introduction of „new public management\", are considered as factors affecting the functionality of the system as well as the decisions of individual scientists (e.g. where to publish their papers). Computer simulation helps to understand the complex interplay of developments at the macro (system) and the micro (actor) level.

Bruce Edmonds
Journal of Artificial Societies and Social Simulation 14 (4) 7

Kyeywords: Philosophy, Science, Simulation, Social Processes, Evolutionary Models, Sociology
Abstract: This briefly reviews some philosophy of science that might be relevant to simulating the social processes of science. It also includes a couple of examples from the sociology of science because these are inextricable from the philosophy.

Christophe Le Page, Nicolas Becu, Pierre Bommel and François Bousquet
Journal of Artificial Societies and Social Simulation 15 (1) 10

Kyeywords: Agent-Based Simulation, Smalltalk, Cormas, Multi-Agent System, Generic Simulation Platform, Renewable Natural Resource Management, Community of Practice, Companion Modeling
Abstract: This paper describes how the Cormas platform has been used for 12 years as an artefact to foster learning about agent-based simulation for renewable resource management. Among the existing generic agent-based simulation platforms, Cormas occupies a tiny, yet lively, place. Thanks to regular training sessions and an electronic forum, a community of users has been gradually established that has enabled a sharing of ideas, practices and knowledge, and the emergence of a genuine community of practice whose members are particularly interested in participatory agent-based simulation.

Adam Arsenault, James Nolan, Richard Schoney and Donald Gilchrist
Journal of Artificial Societies and Social Simulation 15 (1) 11

Kyeywords: Multi-Agent Simulation, Auctions, Agriculture
Abstract: Land acquisition and ownership is an important part of modern agriculture in North America. Given the unique nature of farmland as a good, this paper develops a multi-agent simulation of farmland auction markets in a Canadian context. The model is used to generate data on land transactions between farm agents to determine if a particular auction design or type is better suited to farmland transactions. The simulation uses three different sealed-bid auctions, as well as an English auction. The auctions are compared on the basis of efficiency, stability, and perceived surplus. We find that the form of agent learning about land markets affects both sale price and the variance of sale prices in all of the studied auctions. The second-price-sealed-bid auction generates the most perceived surplus, most equitable share of surplus, and also decreases uncertainty in the common-value element of prices. But on a macroscopic level, it appears that auction choice does not influence market structure or evolution over time.

Teruhiko Yoneyama, Sanmay Das and Mukkai Krishnamoorthy
Journal of Artificial Societies and Social Simulation 15 (1) 5

Kyeywords: Data-Driven Simulation, Epidemiology, Network-Based Simulation, SARS
Abstract: Pandemics can cause immense disruption and damage to communities and societies. Thus far, modeling of pandemics has focused on either large-scale differential equation models like the SIR and the SEIR models, or detailed micro-level simulations, which are harder to apply at a global scale. This paper introduces a hybrid model for pandemics that considers both global and local spread of infection. We hypothesize that the spread of an infectious disease between regions is significantly influenced by global traffic patterns and that the spread within a region is influenced by local conditions. Thus we model the spread of pandemics considering the connections between regions for the global spread of infection and population density based on the SEIR model for the local spread of infection. We validate our hybrid model by carrying out a simulation study for the spread of the SARS pandemic of 2002-2003 using available data on population, population density, and traffic networks between different regions. While it is well-known that international relationships and global traffic patterns significantly influence the spread of pandemics, our results show that integrating these factors into relatively simple models can greatly improve the results of modeling disease spread.

Giovanni Cerulli
Journal of Artificial Societies and Social Simulation 15 (1) 7

Kyeywords: R&D Subsidies, Rivalry Versus Cooperation, Dynamic-Stochastic Games, Simulations
Abstract: By means of a simulated funding-agency/supported-firm stochastic dynamic game, this paper shows that the level of the subsidy provided by a funding (public) agency, normally used to correct for firm R&D shortage, might be severely underprovided. This is due to the "externalities" generated by the agency-firm strategic relationship, as showed by comparing two versions of the model: one assuming "rival" behaviors between companies and agency (i.e., the current setting), and one associated to the "cooperative" strategy (i.e. the optimal Pareto-efficient benchmark). The paper looks also at what "welfare" implications are associated to different degrees of persistency in the funding effect on corporate R&D. Three main conclusions are thus drawn: (i) the relative quota of the subsidy to R&D is undersized in the rival compared to the cooperative model; (ii) the rivalry strategy generates distortions that favor the agency compared to firms; (iii) when passing from less persistent to more persistent R&D additionality/crowding-out effect, the lower the distortion the greater the variance is and vice versa. As for the management of R&D funding policies, we suggest that all the elements favouring greater collaboration between agency and firm objectives may help current R&D support to approach its social optimum.

Hugues Bersini
Journal of Artificial Societies and Social Simulation 15 (1) 9

Kyeywords: Agent-Based Modeling, Object-Orientation Simulation, UML, Complex Systems
Abstract: Although the majority of researchers interested in ABM increasingly agree that the most natural way to program their models is to adopt OO practices, UML diagrams are still largely absent from their publications. In the last 15 years, the use of UML has risen constantly, to the point where UML has become the de facto standard for graphical visualization of software development. UML and its 13 diagrams has many universally accepted virtues. Most importantly, UML provides a level of abstraction higher than that offered by OO programming languages (Java, C++, Python, .Net ...). This abstraction layer encourages researchers to spend more time on modeling rather than on programming. This paper initially presents the four most common UML diagrams - class, sequence, state and activity diagrams (based on my personal experience, these are the most useful diagrams for ABM development). The most important features of these diagrams are discussed, and explanations based on conceptual pieces often found in ABM models are given of how best to use the diagrams. Subsequently, some very well known and classical ABM models such as the Schelling segregation model, the spatial evolutionary game, and a continuous double action free market are subjected to more detailed UML analysis.

Alistair Sutcliffe and Di Wang
Journal of Artificial Societies and Social Simulation 15 (2) 1

Kyeywords: Agent Models, Network Simulations, Health Informatics, Bayesian Models
Abstract: The process by which genes and memes influence behaviour is poorly understood. Genes generally may have a strong influence as predispositions directing individuals towards certain behaviours; whereas memes may have a less direct influence as information inputs to cognitive processes determining behaviour. In certain areas of medical science, knowledge has progressed towards approximate quantification of genetic influences, while social psychology can provide models of mimetic influence as the spread of attitudes. This paper describes a computational model integration of genetic and mimetic influences in a healthcare domain. It models mimetic influences of advertising and health awareness messages in populations with genetic predispositions towards obesity; environmental variables influence both gene expression and mimetic force. Sensitivity analysis using the model with different population network structures is used to investigate the relative force of meme spread and influence.

Mercedes Bleda and Simon Shackley
Journal of Artificial Societies and Social Simulation 15 (2) 2

Kyeywords: Risk Perceptions, Cultural Theory, Simulation Modeling, BSE
Abstract: This paper presents a computer based simulation model which analyses the dynamics of public perceptions of risk using Bovine Spongiform Encephalopathy (BSE) ('mad cow disease') in the UK as a case study. The model is based upon a theoretically-derived understanding of the concept of perception of risk, and employs Cultural Theory and the archetypes it identifies as distinctive forms of social organization and cultural bias in the formation of perceptions. Cultural Theory is used as a theoretical lens for understanding the different interpretations of the risk associated with BSE/nvCJD, the subsequent risk amplification by the media, and the effect of trust and reliance in science and government in their construction. The analysis helps achieve a better understanding of the dynamics of public perceptions of risk, and it is therefore of interest both for academics and policy makers. In particular, the model allows exploring the influence that the occurrence of risk-related events, their media coverage, and trust in government responses has in the process by which people construct their risk perceptions.

Rolf Barth, Matthias Meyer and Jan Spitzner
Journal of Artificial Societies and Social Simulation 15 (2) 5

Kyeywords: Logic of Failure, Management, Methodology, Military, Pitfalls, Simulation Models
Abstract: This paper identifies possible pitfalls of simulation modeling and suggests ways to prevent them. First, we specify five typical pitfalls that are associated with the process of applying simulation models and characterize the \"logic of failure\" (Dörner 1996) behind the pitfalls. Then, we illustrate important aspects of these pitfalls using examples from applying simulation modeling to military and managerial decision making and present possible solutions to them. Finally, we discuss how our suggestions for avoiding them relate to current methodological discussions found in the social simulation community.

Jakob Grazzini
Journal of Artificial Societies and Social Simulation 15 (2) 7

Kyeywords: Statistical Test, Stationarity, Ergodicity, Agent-Based, Simulations
Abstract: This paper illustrates the use of the nonparametric Wald-Wolfowitz test to detect stationarity and ergodicity in agent-based models. A nonparametric test is needed due to the practical impossibility to understand how the random component influences the emergent properties of the model in many agent-based models. Nonparametric tests on real data often lack power and this problem is addressed by applying the Wald-Wolfowitz test to the simulated data. The performance of the tests is evaluated using Monte Carlo simulations of a stochastic process with known properties. It is shown that with appropriate settings the tests can detect non-stationarity and non-ergodicity. Knowing whether a model is ergodic and stationary is essential in order to understand its behavior and the real system it is intended to represent; quantitative analysis of the artificial data helps to acquire such knowledge.

Bo Xianyu
Journal of Artificial Societies and Social Simulation 15 (3) 3

Kyeywords: Prisoner''s Dilemma Game, Complex Network, Adaptive Expectation, Agent-Based Simulation
Abstract: In the spatial prisoner's dilemma game, an agent's strategy choice depends upon the strategies he expects his neighboring agents to adopt. Yet, the expectation of agents in the games has not been studied seriously by the researchers of games in complex networks. The present paper studies the effect of the agents' adaptive expectation on cooperation emergence in the prisoner's dilemma game in complex networks from an agent-based approach. Simulation results show that the agents' adaptive expectation will favor the emergence of cooperation. However, due to agents' adaptive behavior, agents' initial expectation level does not greatly affect the cooperation frequency in the experiments. Simulation results also show that the agents' expectation adjustment speed significantly affects the cooperation frequency. In addition, the initial number of cooperation agents on the network is not a critical factor in the simulations. However, together with a bigger defection temptation, a larger neighborhood size will produce greater cooperation frequency fluctuations in a Barabási and Albert (BA) network, a feature different from that of Watts and Strogatz (WS) small world networks, which can be explained by their different networks degree distributions. Simulation results show that the cooperation frequency oscillating on the WS network is much smaller than that of the BA networks when defection temptation becomes larger. This research demonstrates that agent's adaptive expectation plays an important role in cooperation emergence on complex networks and it deserves more attentions.

Edgar Sioson
Journal of Artificial Societies and Social Simulation 15 (3) 6

Kyeywords: Simulation Testbed, Reputation Systems, Decentralized Currency, Modular Framework, Agent-Based Model
Abstract: We present Flora, a testbed that supports multidimensional fitness and resource modeling. Its main features are evaluation metrics related to population wellbeing, scalable representation of resource diversity, and composability of sociotechnical test scenarios through the TDI framework. We ran simulations to illustrate Flora's use in modeling the effects of using information infrastructures with different component systems. We analyzed the impact of hoarders in the absence of accounting systems, compared the performance of different decentralized currency systems in terms of accounting design features, and modeled the potential impact of reputation systems in deterring detrimental socioeconomic behavior. Among findings were the importance of having resource diversity as well as resources that each could target different fitness dimension needs; the inherent robustness of accounting systems that allow organizations to set budgets independently of centrally issued currency; and the greater effectiveness of buyer-screening compared to seller-screening as a means for influencing malevolent socioeconomic actors.

Ioan Alfred Letia and Radu Razvan Slavescu
Journal of Artificial Societies and Social Simulation 15 (3) 7

Kyeywords: Agent Based Social Simulation, Trust, Reputation, Cognitive Modeling, Multi-Modal Logic
Abstract: We employ a multimodal logic in a decision making mechanism involving trust and reputation. The mechanism is then used in a community of interacting agents which develop cooperative relationships, assess the results against several quality criteria and possibly publish their beliefs inside the group. A new definition is proposed for describing how an agent deals with the common reputation information and with divergent opinions. The definition permits selecting and integrating the knowledge obtained from the peers, based on their perceived trust, as well as on threshold called critical mass. The influence of this parameter and of the number of agents supporting a sentence over its adoption are then investigated.

Michael Meadows and Dave Cliff
Journal of Artificial Societies and Social Simulation 15 (4) 4

Kyeywords: Relative Agreement Model, Opinion Dynamics, Agent-Based Simulation
Abstract: We present a brief history of models of opinion dynamics in groups of agents, and summarise work from the creation of the Bounded Confidence model (Krause 2000; Hegselmann and Krause 2002) through to the more recent development of the Relative Agreement (RA) model (Deffuant et al. 2002; Deffuant 2006). In the RA model, randomly-selected pairs of agents interact, expressing their opinions and their confidence in those opinions; and each agent then updates their own opinion on the basis of the new information. The two seminal RA papers (Deffuant et al. 2002, Deffuant 2006), both published in JASSS, each present simulation results from the RA model that we have attempted to independently replicate. We have surveyed over 150 papers that cite Deffuant et al. 2002, yet have found no prior independent replications of the key empirical results for the RA model presented in the 2002 paper. We have each written a separate implementation of the RA model (one in Java, one in Python, both published in full as appendices to this paper) which we therefore believe to be the first independent replications of the RA model as published in the 2002 JASSS paper. We find that both our implementations of the RA model generate results that are in good agreement with each other, but both of which differ very significantly from those presented by Deffuant et al.. Our results are presented along with an analysis and discussion where we argue from first principles that our results are more plausible than those published in the 2002 JASSS paper. We close with discussion of the relevance of this model, along with future applicability.

Ali Orhan Aydin and Mehmet Ali Orgun
Journal of Artificial Societies and Social Simulation 15 (4) 5

Kyeywords: Reactive-Causal Architecture, Radar Task Simulation
Abstract: The Reactive-Causal Architecture (ReCau) is a cognitive agent architecture which is proposed to simulate human-like intelligence while satisfying the core attributes of believable agents. ReCau combines intentional notion and motivation theories. ReCau agents are entities driven by their unsatisfied needs, to satisfy those needs they act intentionally while satisfaction and dissatisfaction of needs results in affect display. In this paper, the results of a multi-agent based simulation called radar task are presented. With the help of this simulation, ReCau is compared with some other existing agent and cognitive architectures. The results indicate that ReCau provides a highly realistic decision-making mechanism. This architecture; therefore, contributes towards the solution for the development of believable agents.

Jung-Hun Yang and Dick Ettema
Journal of Artificial Societies and Social Simulation 15 (4) 6

Kyeywords: Firm Location, Externalities, Spatial Pattern, Micro-Simulation
Abstract: This paper describes a simulation model of the spatial development of economic activities over time. The key principle addressed is how spatial patterns of economic activity emerge from decisions of individual firms, which are in turn influenced by the existing spatial configuration. A stylized simulation is presented, in which two types of firms grow at different rates, giving rise to split offs and spatial relocations. The influence of the spatial pattern on individual firms' decisions is implemented in various ways, related to well-known effects such as Jacobs and Marshall externalities described in the economic literature and congestion effects. We demonstrate that different assumptions about the spatial scale of these externalities lead to different spatial configurations. Function concentration (Marshall effects) is more likely to lead to the emergence of subcentres with a specific specialisation. However, the spatial scale of the market and agglomeration effects matters. In particular, if Marshall advantages stretch out over a longer distance, more subcentres emerge. Somewhat surprisingly, congestion seems to have a minor impact on the emerging patterns. The simulation outcomes are intuitively plausible, suggesting that micro-simulation is a promising tool for developing forecasting models to support spatial and economic policies. However, they also articulate the need for validation of the behavioural decision rules, in particular by investigating how growth rates and the spatial scale of externalities differs between different industrial sectors.

Guillermo Montes
Journal of Artificial Societies and Social Simulation 15 (4) 8

Kyeywords: NetLogo, Agent Based Simulation, Racial Disparities, Achievement Gap, United States
Abstract: This paper presents an agent-based model of the standard U.S. k-12th grade classroom using NetLogo. By creating an artificial society, we identify the casual implications of the same-race effect (a moderate sized academic boost to students whose teachers have the same race) on the national educational achievement trends. The model predicts sizeable achievement gaps at the national level, consistent in size with those documented by the US National Report Card (NAEP) stemming from moderate sized same race effects. In addition, matching effects are found to be a source of increased heterogeneity in academic performance for the minority group. These results hold for all teacher-student matching phenomena and have implications for educational policy at the aggregate level. Using artificial societies to disentangle the aggregate effects of hypothesized causes of the achievement gap is a promising strategy that merits further research.

Flaminio Squazzoni and Niccolò Casnici
Journal of Artificial Societies and Social Simulation 16 (1) 10

Kyeywords: JASSS, Social Simulation, Bibliometric Analysis, Impact, Inter-Journal Citations
Abstract: This paper examines the bibliometric impact of JASSS on other ISI- and Scopus-indexed sources by examining inward and outward citations and their inter-relation. Given the prestige of JASSS, this analysis can measure the growth and dynamics of social simulation and give us an indication of the direction in which social simulation is moving. Results show that the impact of JASSS is higher in computer sciences, physics and ecology than it is in the social sciences, even though JASSS-indexed articles tend to be more concerned with social science-related topics. Looking at inter-journal citations revealed an interesting citation structure: JASSS collected its largest percentage of citations from non-social science-focused journals while directing more citations within its own articles toward works published in social science journals. On the one hand, this would confirm that social simulation is not yet recognised in the social science mainstream. On the other hand, this may indicate that the cross-disciplinary nature of JASSS allows it to promulgate social science theories and findings in other distant communities.

Guillaume Deffuant, Gérard Weisbuch, Frederic Amblard and Thierry Faure
Journal of Artificial Societies and Social Simulation 16 (1) 11

Kyeywords: Opinion Dynamics, Social Simulation, Agents Based Model
Abstract: Meadows and Cliff (2012) failed to replicate the results of Deffuant et al. (2002) and concluded that our paper was wrong. In this note, we show that the conclusions of Meadows and Cliff are due to a wrong computation of indicator y, which was not fully specified in our 2002 paper. In particular, Meadows and Cliff compute indicator y before model convergence whereas this indicator should be computed after model convergence.

Emmanuel Dubois, Olivier Barreteau and Véronique Souchère
Journal of Artificial Societies and Social Simulation 16 (1) 2

Kyeywords: Agent-Based Social Simulation, Role Playing Game, Companion Modelling, Attitude-Behaviour Relations, Attitude Change, Game Setting Effects
Abstract: Role playing games (RPGs) can be used as participatory simulation methods for environmental management. However, researchers in the field need to be aware of the influence of the game settings on participants' behavioural patterns and attitudes, before fine tuning the design and use of their games. We developed an agent-based model (CauxAttitude) to assess the framing induced by the conditions of implementation of a specific game, named CauxOpération, on possible changes in participants' attitudes. We designed CauxAttitude on the basis of social psychology theories that describe relations between attitudes and behaviours, as well as on observations of CauxOpération sessions. In this paper, we describe how the model behaved according to variations in the initialization of the parameters, our aim being to explore the effects of subjective choices concerning model design and implementation. The results of our simulations enabled us to identify effects of game settings we explored, including the choice of the population of participants or of the number of participants made by the game designer. Our results also revealed the underlying mechanisms that explain the effects of game settings. These provide clues to the game designer on how to manage them.

Lyndon Walker and Peter Davis
Journal of Artificial Societies and Social Simulation 16 (1) 6

Kyeywords: Marriage, Ethnicity, Homophily, Simulation
Abstract: Choice mechanisms and social networks, including \"marriage markets\", seem well-suited to be modelled using agent-type simulations. Few real-world empirical examples are available in the public literature, particularly those using human populations of size. We reviewed partnership models in both the micro-simulation and agent-based literatures. We then empirically implemented an algorithm derived from two established models using inter-censal data on first partnerships in New Zealand over the period 1981-2006. The purpose of the exercise was to test the robustness of different parameter settings and to determine whether a model simulating partnership selection among eligible never-married young adults at one census period is feasible for predicting patterns of partnership, co-habitation and marriage at the next. Varying simulation time and social network size parameters of the model showed that patterns of ethnic partnering could be consistently produced and were not dependent on these model settings. Examining the different scoring methods showed that age similarity, education similarity, and previous partnering patterns could produce partnership patterns similar to those seen in the census. The simulation produced patterns of ethnic partnering similar to those seen in the census and seemed robust to different parameter settings. To further improve these results, an optimised combination of the scoring components is proposed. The simulations also provided preliminary evidence of ethnic preferences in the New Zealand marriage market.

Amineh Ghorbani, Pieter Bots, Virginia Dignum and Gerard Dijkema
Journal of Artificial Societies and Social Simulation 16 (2) 9

Kyeywords: Modelling Language, Model-Driven Engineering, Institutions, Social Simulation, Meta-Model
Abstract: In this paper we introduce and motivate a conceptualization framework for agent-based social simulation, MAIA: Modelling Agent systems based on Institutional Analysis. The MAIA framework is based on Ostrom's Institutional Analysis and Development framework, and provides an extensive set of modelling concepts that is rich enough to capture a large range of complex social phenomena. Developing advanced agent-based models requires substantial experience and knowledge of software development knowledge and skills. MAIA has been developed to help modellers who are unfamiliar with software development to conceptualize and implement agent-based models. It provides the foundation for a conceptualization procedure that guides modellers to adequately capture, analyse, and understand the domain of application, and helps them report explicitly on the motivations behind modelling choices. A web-based application supports conceptualization with MAIA, and outputs an XML file which is used to generate Java code for an executable simulation.

Naoki Shiba
Journal of Artificial Societies and Social Simulation 16 (3) 11

Kyeywords: Social Simulation, Agent-Based Models (ABM), Theorem-Proof Approach, Mate-Search Problem, Two-Sided Matching, Job Matching
Abstract: This paper discusses an extended version of the matching problem which includes the mate search problem; this version is a generalization of a traditional optimization problem. The matching problem is extended to a form of the asymmetric two-sided matching problem. An agent-based simulation model is built and simulation results are presented. Todd and Miller (1999) simulated the two-sided matching problem in a symmetric setting. In his model, there are the same number of agents in both parties (groups), each of whom has his/her own mate value. Each agent in a party tries to find his/her mate in the other party, based on his/her candidate's mate value and his/her own aspiration level for his/her partner's mate value. Each agent learns his/her own mate value and adjusts his/her aspiration level through the trial period (adolescence). Todd and Miller (1999) tried several search rules and learning mechanisms that are symmetric for both parties. In the present paper, Todd and Miller's (1999) model is extended to an asymmetric setting where the two parties have different numbers of agents, and the search rule and the learning mechanism for the two parties differ. Through the simulation, the search rules and the learning mechanisms which were identified to be appropriate in a symmetric setting are revealed to be inappropriate in the asymmetric setting and the reason why this is so is discussed. Furthermore, some general facts are derived using a mathematical theorem-proof approach. Some of these facts are used to direct a revision of the model, and a revised simulation model is presented. An implication is obtained for practical situations in asymmetric matching setting. For example, in the job hunting case, if job applicants want to finish their job hunting successfully, they should be modest at the beginning of the hunt.

Andrzej Nowak, Agnieszka Rychwalska and Wojciech Borkowski
Journal of Artificial Societies and Social Simulation 16 (3) 12

Kyeywords: Computer Simulations, Mental Models, Benefits of Simulations, Recommendations for Modeling
Abstract: Computer simulations, one of the most powerful tools of science, have many uses. This paper concentrates on the benefits to the social science researcher. Based on our, somewhat paradoxical experiences we had when working with computer simulations, we argue that the main benefit for the researchers who work with computer simulations is to develop a mental model of the abstract process they are simulating. The development of a mental model results in a deeper understating of the process and in the capacity to predict both the behavior of the system and its reaction to changes of control parameters and interventions. By internalizing computer simulations as a mental model, however, the researcher also internalizes the limitations of the simulation. Limitations of the computer simulation may translate into unconscious constrains in thinking when using the mental model. This perspective offers new recommendations for the development of computer simulations and highlights the importance of visualization. The recommendations are different from the recommendations for developing efficient and fast running simulations; for example, to visualize the dynamics of the process it may be better for the program to run slowly.

Samer Hassan, Javier Arroyo, José Manuel Galán, Luis Antunes and Juan Pavón
Journal of Artificial Societies and Social Simulation 16 (3) 13

Kyeywords: Forecasting, Guidelines, Prediction, Agent-Based Modelling, Modelling Process, Social Simulation
Abstract: This paper presents a set of guidelines, imported from the field of forecasting, that can help social simulation and, more specifically, agent-based modelling practitioners to improve the predictive performance and the robustness of their models. The presentation starts with a discussion on the current debate on prediction in social processes, followed by an overview of the recent experience and lessons learnt from the field of forecasting. This is the basis to define standard practices when developing agent-based models under the perspective of forecasting experimentation. In this context, the guidelines are structured in six categories that correspond to key issues that should be taken into account when building a predictor agent-based model: the modelling process, the data adequacy, the space of solutions, the expert involvement, the validation, and the dissemination and replication. The application of these guidelines is illustrated with an existing agent-based model. We conclude by tackling some intrinsic difficulties that agent-based modelling often faces when dealing with prediction models.

Sabine Zinn, Jan Himmelspach, Adelinde M. Uhrmacher and Jutta Gampe
Journal of Artificial Societies and Social Simulation 16 (3) 5

Kyeywords: Continuous-Time Microsimulation, Framework, Plug-In, Demography, Modeling, Simulation
Abstract: Often new modeling and simulation software is developed from scratch with no or only little reuse. The benefits that can be gained from developing a modeling and simulation environment by using (and thus reusing components of) a general modeling and simulation framework refer to reliability and efficiency of the developed software, which eventually contributes to the quality of simulation experiments. Developing the tool Mic-Core which supports continuous-time micro modeling and simulation in demography based on the plug-in-based modeling and simulation framework JAMES II will illuminate some of these benefits of reuse. Thereby, we will focus on the development process itself and on the quality of simulation studies, e.g., by analyzing the impact of random number generators on the reliability of results and of event queues on efficiency. The "lessons learned" summary presents a couple of insights gained by using a general purpose framework for M&S as a base to create a specialized M&S software.

Hong Zhang, Yue Wang, Yin Lin, Yang ZHANG and Michael J. Seiler
Journal of Artificial Societies and Social Simulation 16 (3) 8

Kyeywords: Blocking Effect, Transaction Costs, Housing Consumption, Household Mobility, Simulation Analysis
Abstract: To examine the blocking effect of transaction costs on household mobility, we construct a housing consumption model including transaction costs and adopt an analog simulation methodology, analyzing how changes in household income and home prices influence household consumption, savings decisions and the transaction costs blocking effect. We find that changes in housing demand are the fundamental cause of the blocking effect of transaction costs. The more demand changes, the greater the blocking effect is. Besides, increased volatility in home prices worsens the household mobility problem with regards to the blocking effect of transaction costs, while a change in household income does not impact the blocking effect of transaction costs on housing consumption. To expand housing consumption, our findings suggest active measures that should be taken by policymakers to reduce transaction costs and stabilize home prices.

Annie Waldherr and Nanda Wijermans
Journal of Artificial Societies and Social Simulation 16 (4) 13

Kyeywords: Social Simulation, Agent-Based Modelling, Rejective Criticism, Constructive Feedback, Communication, Peer Support
Abstract: When talking to fellow modellers about the feedback we get on our simulation models the conversation quickly shifts to anecdotes of rejective scepticism. Many of us experience that they get only few remarks, and especially only little helpful constructive feedback on their simulation models. In this forum paper, we give an overview and reflections on the most common criticisms experienced by ABM modellers. Our goal is to start a discussion on how to respond to criticism, and particularly rejective scepticism, in a way that makes it help to improve our models and consequently also increase acceptance and impact of our work. We proceed by identifying common criticism on agent-based modelling and social simulation methods and show where it shifts to rejection. In the second part, we reflect on the reasons for rejecting the agent-based approach, which we mainly locate in a lack of understanding on the one hand, and academic territorialism on the other hand. Finally, we also give our personal advice to socsim modellers of how to deal with both forms of rejective criticism.

Roger Waldeck
Journal of Artificial Societies and Social Simulation 16 (4) 14

Kyeywords: Social Emotions, Norms, Prisoner, Spatial Interaction Structures, Segregation, Agent-Based Simulation
Abstract: Observations in experiments show that players in a prisoner's dilemma may adhere more or less to a cooperative norm. Adherence is defined by the intensity of pro-social emotions, like guilt, of deviating from the norm. Players consider also payoffs from defection as a motive to deviate. By combining both incentives, the modeling may explain conditional cooperation and the existence of polymorphic equilibria in which cooperators and defectors coexist. We then show by the use of simulations, that local interaction structures may produce segregation and the appearance of cooperative zones under these conditions.

Christian Garavaglia, Franco Malerba, Luigi Orsenigo and Michele Pezzoni
Journal of Artificial Societies and Social Simulation 16 (4) 5

Kyeywords: Simulation, Industrial Dynamics, Innovation, Market Structure, Pharmaceuticals
Abstract: This paper examines the evolution of the pharmaceutical industry. After a brief discussion of the main stylised facts about the industry, we present a history-friendly model that aims at capturing the underlining mechanisms and the logic that guides the evolution of this industry. Simulation results show the mechanisms and dynamic processes linking the patterns of innovation, demand structure, and concentration.

Nicolas Becu, Christine Raimond, Eric Garine, Marc Deconchat and Kouami Kokou
Journal of Artificial Societies and Social Simulation 17 (1) 1

Kyeywords: Agent-Based Spatial Simulation, Social Resilience, Cameroon, Landscape Modeling, Shifting Cultivation
Abstract: This paper presents an agent-based spatial simulation of shifting cultivation applied to savannah landscape in North-Cameroon (Duupa ethnic community). The model is based on empirical rules and was developed by a team who seek to create interdisciplinary dynamics by combining domain specific approaches to the same subject. The manner in which the model is described in this paper reflects the interdisciplinary processes that guided its development. It is made up of four domain-specific modules - demography, agriculture, savannah regrowth and social rules - which converge to form a fifth one, i.e., the evolution of the mosaic of cultivated fields. The focus is on how the spatial organization of landscapes results of environmental and social interactions. Two scenarios are presented in this paper. The first simulates the transformation of savannah woodland into a shifting cultivation savannah landscape. The second simulates changes in the landscape and socio-demographic structure of a Duupa village over a 60-year period. The simulation results are used to identify some of the key aspects of the socio-environmental interactions and help to explain why at large spatial scales and over a long period of time, the composition and structure of a landscape appear rather stable. For instance, it is well known that demography plays a key role in both social and environmental dynamics of shifting cultivation systems. Yet, in the case of the Duupa system, we show that social resilience can be acquired through interactions between demographic cycles of rising and falling population levels and a socioeconomic redistribution system. Finally, we compare the model developed with other shifting cultivation models and provide some insights on future developments.

Ismail Saglam
Journal of Artificial Societies and Social Simulation 17 (1) 12

Kyeywords: Mate Choice, Mate Search, Simple Heuristics, Agent-Based Simulation, Behavioral Stability, Equilibrium Strategies
Abstract: Human mate choice is a boundedly rational process where individuals search for their mates without appealing to optimization techniques due to informational, computational and time constraints. A seminal work by Todd and Miller (1999) models this search process using simple heuristics, i.e. decision rules that adjust individuals' aspiration levels adaptively. To identify the best heuristic among a number of alternatives, they consider fixed measures of success. In this paper, we deal with the same identification problem by examining whether these heuristics would be favored by behavioral selection. To this aim, we extend the two-phase search model of Todd and Miller (1999) to a behavioral (strategic-form) game in which each individual in the population is a distinct player, each player's strategy space contains the same four heuristics (adjustment rules), and the payoff of each player is measured by the likelihood of his/her mating. For this game, we ask whether any strategy profile at which the whole population plays the same heuristic can be behaviorally stable with respect to the Nash equilibrium concept. Our simulations show that the unanimous use of the Take the Next Best Rule by the whole population never becomes an equilibrium in the simulation range of adolescence lengths. While the Adjust Relative Rule is found to be behaviorally stable for a wide part of the simulation range, especially for medium to high adolescence lengths, the rules Adjust Up/Down and Adjust Relative/2 are favored by behavioral selection for a small part of the simulation range and only when the adolescence is long and short, respectively. We make the final evaluation of the four heuristics with respect to a new success measure that integrates a behavioral stability metric proposed in this paper with two metrics of Todd and Miller (1999), namely the likelihood and the assortativeness of the mating generated by the heuristic in use.

Francesco Pizzitutti, Carlos F. Mena and Stephen J. Walsh
Journal of Artificial Societies and Social Simulation 17 (1) 14

Kyeywords: Spatial Agent Based Model and Simulation, Galapagos Islands, Tourist Destination Dynamics
Abstract: Currently tourism is the main driver of change in the Galapagos Islands, affecting the social, terrestrial, and marine sub-systems. Tourism also has direct and indirect consequences for the unique archipelago’s natural habitats and for the human well-being. Describing the mechanisms that drive and affect most the tourism development in Galapagos is a preliminary condition to developing a better understanding of the interaction structure of factors that shape the Galapagos archipelago as a social-ecological complex system. In this paper, we present a first attempt to represent the touristic market in Galapagos trough an Agent Based Model (ABM) of touristic activity, focusing on touristic offers, reservations, and touristic activities. The model is based on an individual-based representation of tourists’ consumption preferences and touristic accommodation offers in the Galapagos Islands. Tourist agents are created to mimic the real world by assigning average characteristics of individuals who visit the Galapagos Archipelago of Ecuador. The accommodation offers (i.e., hotels and cruises) are generated in accordance with actual conditions derived from data collected through field surveys. The model includes a market agent that can change the prices, create and delete accommodation offers following an evolutionary algorithm. We carried out preliminary simulations that show a close agreement between real world data and model outputs. Furthermore we used the model to generate three “what if” scenarios in order to study how emergent patterns in the touristic market in Galapagos are affected by changes in the archipelago environment. In this way we illustrate how the model can be used as a useful tool to help public policy makers to explore the consequences of their decisions.

Alessandro Pluchino, Cesare Garofalo, Giuseppe Inturri, Andrea Rapisarda and Matteo Ignaccolo
Journal of Artificial Societies and Social Simulation 17 (1) 16

Kyeywords: Agent-Based Simulations, Carrying Capacity, Pedestrian Dynamics, Evacuation Dynamics
Abstract: In order to analyse the behaviour of pedestrians at the very fine scale, while moving along the streets, in open spaces or inside a building, simulation modelling becomes an essential tool. In these spatial environments, simulation requires the ability to model the local dynamics of individual decision making and behaviour, which is strongly affected by the geometry, social preferences, local and collective behaviour of other individuals. The dy-namics of people visiting and evacuating a museum offers an excellent case study along this line. In this paper we present an agent-based simulation of the Castello Ursino museum in Catania (Italy), evaluating its carrying capacity in terms of both satisfaction of the visitors in regime of non-emergency dynamics and their safety under alarm conditions.

Hong Zhang and Yang Li
Journal of Artificial Societies and Social Simulation 17 (1) 18

Kyeywords: Resale Housing Market, Search Behavior, Search Model, Agent-Based Simulation, Sensitivity Analysis
Abstract: In the paradigm of the search theory, we established the search model applicable to the characteristics of China's resale housing market, by modeling the search behavior for buyer and seller, respectively. Setting the parameters based on the Beijing housing market survey in August 2012, we implemented agent-based simulation to study the dynamics of the search behavior measured by search intensity and search time. Sensitivity test was also used to analyze the determinants of the search behavior for trading agents. The simulation results validate the idiosyncratic feature of the agent's search behavior, which is consistent with theoretical analysis. The increase of matching efficiency promotes the agents' search intensities, but the higher unit search cost can reduce the agents' search intensities. The buyer's search behavior is more sensitive to the change in the market tightness ratio. Brokerage service lowers the transaction price and lessens the agents' search intensities. Sensitivity test further reveals that, the matching efficiency and the market tightness ratio play very important role in improving housing market liquidity. The changes in the search cost and the broker commission rate can reduce the agents' search intensities significantly and there are critical turning points at which the abrupt change occurs.

Birnur Özbaş, Onur Özgün and Yaman Barlas
Journal of Artificial Societies and Social Simulation 17 (1) 19

Kyeywords: Real Estate Modeling, Housing Cycles, Price Oscillations, System Dynamics, Socio-Economic Simulation
Abstract: The purpose of this study is to model and analyze by simulation the dynamics of endogenously created oscillations in real estate (housing) prices. A system dynamics simulation model is built to understand some of the structural sources of cycles in the key housing market variables, from the perspective of construction companies. The model focuses on the economic balance dynamics between supply and demand. Because of the unavoidable delays in the perception of the real estate market conditions and construction of new buildings, prices and related market variables exhibit strong oscillations. Two policies are tested to reduce the oscillations: decreasing the construction time, and taking into account the houses under construction in starting new projects. Both policies yield significantly reduced oscillations, more stable behaviors.

Rory Sie, Peter B. Sloep and Marlies Bitter-Rijpkema
Journal of Artificial Societies and Social Simulation 17 (1) 3

Kyeywords: Coalition Formation, Networked Innovation, Creativity, Simulation of Social Networks, Social Behaviour, Complex Networks
Abstract: The present article uses agent-based social simulation to study rational behaviour in networked innovation. A simulation model that includes network characteristics and network participant’s characteristics is run using parameter sweeping, yielding 1450 simulation cases. The notion of coalitions was used to denote partnerships in networked innovation. Coalitions compete against each other and several variables were observed for winning coalitions. Close analysis of the variations and their influence on the average power per winning coalition was analysed using stepwise multiple regression analysis. The analysis brought forward two main conclusions. First, as average betweenness centrality per winning coalition increases, the average power per winning coalition decreases. This implies that having high betweenness centrality as a network participant makes it easier to build a successful coalition, as a coalition needs lower average power to succeed. Second, as the number of network participants increases, the average power per winning coalition decreases. This implies that in a larger network, it may be easier to form a successful coalition. The results form the basis for the development of a utility-based recommendation system that helps people choose optimal partners in an innovation network.

Elio Marchione, Shane D Johnson and Alan Wilson
Journal of Artificial Societies and Social Simulation 17 (2) 9

Kyeywords: Maritime Piracy, Crime, Map Generation, Simulation, Agent-Based Modelling
Abstract: This paper presents a model to generate dynamic patterns of maritime piracy. Model details, outputs and calibration are illustrated. The model presented here is a tool to estimate the number of pirates and their area of action. The Gulf of Aden is considered as a case study, and data on pirate attacks, vessels routes and flows through the Gulf of Aden in the year 2010 are used to build the model. Agent-based modelling is employed to simulate pirate, vessel and naval forces behaviours.

Klaus Hamberger and Floriana Gargiulo
Journal of Artificial Societies and Social Simulation 17 (3) 2

Kyeywords: Kinship, Marriage Alliance, Agent Based Simulation, Observer Bias, Fieldwork, Ebrei
Abstract: The morphological properties of genealogical and marriage alliance networks constitute a key to the understanding of matrimonial behavior and social norms, in particular where these norms have not been explicitly formalized. Their analysis, however, faces a major difficulty: the actual datasets which allow researchers to reconstruct kinship and alliance networks are generally subject to a marked observer bias, if only due to limitations of observer mobility and/or informant memory. This paper presents an agent based simulation method destined to evaluate the impact of this bias on some key indicators of kinship and alliance networks (such as matrimonial circuit frequencies). The method consists in explicitly simulating the exploration of a given network by a virtual observer, the bias being introduced by the observer’s inclination for choosing informants who are more or less closely related to each other. The article presents the model for genealogical and for alliance networks, applies it to a series of artificial networks exhibiting some characteristic morphological patterns, and discusses the divergence of observed from real patterns for different kinds and degrees of observer bias. The methods presented have been implemented in the free software Puck 2.0.

Pablo Lucas, Angela C.M. de Oliveira and Sheheryar Banuri
Journal of Artificial Societies and Social Simulation 17 (3) 5

Kyeywords: Social Preferences, Group Composition, Beliefs, Agent-Based Simulation
Abstract: Behavioural economics highlights the role of social preferences in economic decisions. Further, populations are heterogeneous, suggesting that the composition of social preference types within a group may impact the ability to sustain voluntary public goods contributions. We conduct agent-based simulations of contributions in a public goods game, varying group composition and the weight individuals place on their beliefs versus their underlying social preference type. We then examine the effect of each of these factors on contributions. We find that social preference heterogeneity negatively impacts provision over a wide range of the parameter space, even controlling for the share of types in a group.

Márcia Baptista, Carlos Roque Martinho, Francisco Lima, Pedro A. Santos and Helmut Prendinger
Journal of Artificial Societies and Social Simulation 17 (3) 7

Kyeywords: Agent-Based Modeling, Business Simulation, Consumer Behavior, Learning Processes
Abstract: Artificial society simulations may provide unprecedented insight into the intricate dynamics of economic markets. Such an insight may help solve the well-known black-box dilemma of business simulations, where designers prefer model concealment over model transparency. The core contribution of this work is an agent-based business simulation that models the marketplace as an artificial society of consumers. In the simulation, users assume the role of a store owner playing against an artificial intelligence competitor. The simulation can be accessed via a graphical user interface that animates the decision behavior of consumers. Consumers are modeled as agents with concrete beliefs, intentions and desires that act to maximize their utility and accomplish their purchase plans. We claim that unlike the classical equation-based approach, the visualization of market dynamics facilitated by our agent-based approach can provide important information to the user. We hypothesize that such information is key to understanding several economic concepts. To validate our hypothesis, we conducted an experiment with 30 users, where we compared the effects of the graphical animation of the market. Our results indicate that the agent-based approach has better learning outcomes both at the level of users' subjective self-assessment and at the level of objective performance metrics and knowledge acquisition tests. As a secondary contribution, we demonstrate by example how simple codification rules at the level of the utility functions of agents allow the emergence of diverse macroeconomic behavior of a two-product duopoly.

Chung-Yuan Huang and Tzai-Hung Wen
Journal of Artificial Societies and Social Simulation 17 (3) 8

Kyeywords: Social Influence, Private Acceptance, Public Compliance, Theory of Reasoned Action, Cognitive Dissonance Theory, Agent-Based Simulation
Abstract: Pluralistic ignorance, a well-documented socio-psychological conformity phenomenon, involves discrepancies between private attitude and public opinion in certain social contexts. However, continuous opinion dynamics models based on a bounded confidence assumption fail to accurately model pluralistic ignorance because they do not address scenarios in which non-conformists do not need to worry about holding and expressing conflicting opinions. Such scenarios reduce the power of continuous opinion dynamics models to explain why certain groups doubt or change their opinions in response to minority views. To simulate the effects of (a) private acceptance of informational social influence and (b) public compliance with normative social influence on pluralistic ignorance and minority influences, we have created an agent-based simulation model in which attitude and opinion respectively represent an agent's private and expressed thoughts. Results from a series of simulation experiments indicate model validity equal to or exceeding those of existing opinion dynamics models that are also based on the bounded confidence assumption, but with different dynamics and outcomes in terms of collective opinion and attitude. The results also support the use of our proposed model for computational social psychology applications.

Bill Kaye-Blake, Chris Schilling and Elizabeth Post
Journal of Artificial Societies and Social Simulation 17 (4) 5

Kyeywords: Agriculture, Interdisciplinary Research, Multi-Agent Simulation, Validation, Agent-Based Model
Abstract: This paper describes the process and results of validating a simulation model of agriculture for a region in New Zealand. Validation is treated as a process, in which simulation models are made useful for specific purposes by making them conform to observed historical trends and relationships. In this case, the model was calibrated to reproduce the year-by-year conversion to dairying from 1993 to 2012 in Southland, New Zealand. This was achieved by holding constant some elements of the simulation model, based on economic theory or data, and by running simulations on a range of values for two key parameters. The paper describes the model and process, and demonstrates that empirical validation is possible if approached pragmatically with a view to the intended use of the model. Important elements are: using stylised facts to limit the parameter space ex ante, establishing the range of model outcomes and focusing on the most likely parameter space, focusing the search for parameter values where there is the greatest uncertainty, and using historical data to calibrate models.

Rodrigo Castro and Pablo Jacovkis
Journal of Artificial Societies and Social Simulation 18 (1) 13

Kyeywords: Global Models, Social Processes, Complex Systems, History of Science, Computer Simulation, Latin American Modeling
Abstract: During the 1960s but mainly in the 1970s, large mathematical dynamic global models were implemented in computers to simulate the entire world, or large portions of it. Several different but interrelated subjects were considered simultaneously, and their variables evolved over time in an attempt to forecast the future, considering decades as time horizons. Global models continued to be developed while evidencing an increasing bias towards environmental aspects, or at least the public impact of models with such a focus became prevalent. In this paper we analyze the early evolution of computer-based global modeling and provide insights on less known pioneering works by South American modelers in the 1960s (Varsavsky and collaborators). We revisit relevant methodological aspects and discuss how they influenced different modeling endeavors. Finally, we overview how distinctive systemic approaches in global modeling evolved into the currently well-established discipline of complex systems.

Ozge Dilaver
Journal of Artificial Societies and Social Simulation 18 (1) 15

Kyeywords: Mixed Methods, Grounded Theory, Context, Rules, Fieldwork, Simulation Experiments
Abstract: This paper introduces a mixed-method research design for investigating complexity of social reality. The research design integrates grounded theory (Glaser and Strauss, 1967) and social simulation and is therefore called grounded simulation (GS). GS starts with in-depth investigations of complex social phenomena from perspectives of people who experience them. These investigations follow principles of grounded theory and enquire into contexts that research participants describe and the way they make sense of action in these contexts. Data analysis progresses inductively and outwards, from narratives of people who are at the centre of the phenomena to emerging constructs and theories. While the grounded theory fieldwork would have its own research outputs, its selected findings can be then carried to agent-based models for further investigation of social complexity. By representing social and economic agents, their contexts and actions as closely as possible, GS shortens the distance between research participants, who have real life experiences of the subject being modelled, and the virtual agents. Knowledge production in social simulation progresses generatively and upwards, moving from interactions at the individual level to emergent properties at the macro-level. GS experiments are thus suitable for studying the societal implications of meanings that emerge from the data collected in grounded theory. The paper illustrates how this research design can be used, by referring to a GS study on diffusion of innovations.

Sukaina Bharwani, Mònica Coll Besa, Richard Taylor, Michael Fischer, Tahia Devisscher and Chrislain Kenfack
Journal of Artificial Societies and Social Simulation 18 (1) 3

Kyeywords: Knowledge Elicitation, Decision-Making, Climate Adaptation, Verification and Validation, Social Simulation, Tacit Knowledge
Abstract: This paper describes a participatory and collaborative process for formalising qualitative data, using research from southeast Cameroon, how these results can provide input to an social simulation model, and what insights they can provide in better understanding decision-making in the region. Knowledge Elicitation Tools (KnETs) have been used to support a body of existing research on local strategies that build community adaptive capacity and support sustainable forest management under a range of socio-environmental and climatic stressors. The output of this approach is a set of decision rules which complements previous analysis of differentiated vulnerability of forest communities. Improvements to the KnETs methodology, such as new statistical measurements, make it easier to generate inputs for a social simulation model, such as agent attributes and heterogeneity, as well as informing which scenarios to prioritise during model development and testing. The KnETs process served as a vehicle to structure a large volume of empirical data, to identify the most salient drivers of decision-making amongst different actors, to uncover tacit knowledge and to make recommendations about which strategic interventions should be further explored in a social simulation and by local organizations planning interventions. It was notable that there were many common rule drivers for men and women from the same households, though they participated in the game-interviews separately. At the same time, though strategies were common to both poor and better-off farmers, differences lay in the package of strategies chosen – the number and type of strategies as well the drivers factors – and how they were prioritised with respect to each farmer’s goal.

Christophe Le Page, Kadiri Serge Bobo, Towa Olivier William Kamgaing, Bobo Fernanda Ngahane and Matthias Waltert
Journal of Artificial Societies and Social Simulation 18 (1) 8

Kyeywords: Bushmeat Hunting, Participatory Simulation, Community-Based Wildlife Management, Companion Modelling, Qualitative Data
Abstract: An agent-based model (ABM) representing snare trapping of blue duikers (Cephalophus monticola) was co-designed and used with local populations to raise their awareness about the sustainability of bushmeat hunting activities in the region of the Korup National Park (South-West Cameroon). Village meetings based on interactive simulations with a stylized scale model were structured in three successive steps. During the first step, an abstract representation of a village surrounded by a portion of forest was co-designed by directly manipulating the computer interface displaying a spatial grid. Then, knowledge about the live-cycle traits and the behavior of blue duikers was shared through the demonstration of the individual-based population dynamics module of the ABM. The objective of the second step, introducing the hunting module of the ABM, was to elicit snare trapping practices trough interactive simulation and to calibrate the hunting module by setting a value for the probability of a blue duiker to be caught by a snare trap. In a third step, a more realistic version of the ABM was introduced. The seven villages included in the process were located in the GIS-based spatial representation, and the number of “Hunter” agents for each village in the ABM was set according to the results of a survey. The demonstration of this realistic version triggered discussion about possible management scenarios, whose results obtained with the finalized version of the ABM will be discussed during next round of village meetings. We present the pros and cons of the method consisting in using at an early stage of the process interactive simulations with stylized scale models to specify empirically-based agent-based models.

Tommaso Venturini, Pablo Jensen and Bruno Latour
Journal of Artificial Societies and Social Simulation 18 (2) 11

Kyeywords: Simulations, Big Data, Social Science, Micro Macro, Science Policy, Modeling
Abstract: In the last few years, electronic media brought a revolution in the traceability of social phenomena. As particles in a bubble chamber, social trajectories leave digital trails that can be analyzed to gain a deeper understanding of collective life. To make sense of these traces a renewed collaboration between social and natural scientists is needed. In this paper, we claim that current research strategies based on micro-macro models are unfit to unfold the complexity of collective existence and that the priority should instead be the development of new formal tools to exploit the richness of digital data.

Caroline Krejci and Benita Beamon
Journal of Artificial Societies and Social Simulation 18 (2) 19

Kyeywords: Food Supply Chains, Sustainable Agriculture, Coordination, Agent-Based Modeling, Farmer Decision Making, Multi-Agent Simulation
Abstract: To increase profitability, farmers often decide to form strategic partnerships with other farmers, pooling their resources and outputs for greater efficiency and scale. These coordination decisions can have far-reaching and complex implications for overall food supply chain structural emergence, which in turn impacts system outcomes and long-term sustainability. In this paper, we describe an agent-based model that explores the impacts of farmer coordination decisions on the development of food supply chain structure over time. This model focuses on one type of coordination mechanism implementation method, in which coordinated farmer groups produce a single crop type and combine their yields to achieve economies of scale. The farmer agents’ decisions to coordinate with one another depend on their evaluation of the tradeoff between their autonomy and the expected economic benefits of coordination. Each coordination decision is a bilateral process in which the terms of group reward sharing are negotiated. We capture the effects of farmers’ size, income, and autonomy premia, as well as volume-price relationships and group profit-sharing rules, on the rate of farmer coordination and the number and size of groups that form. Results indicate that under many conditions, coordination groups tend to consolidate over time, which suggests implications for overall supply chain structural resilience.

Mason Wright and Pratim Sengupta
Journal of Artificial Societies and Social Simulation 18 (2) 3

Kyeywords: Multi-Agent Models, Lobbying, Public Choice, Bounded Rationality, Voting Behavior, Social Simulation
Abstract: In this paper, we investigate the interactions among oligarchs, political parties, and voters using an agent-based modeling approach. We introduce the OLIGO model, which is based on the spatial model of democracy, where voters have positions in a policy space and vote for the party that appears closest to them, and parties move in policy space to seek more votes. We extend the existing literature on agent-based models of political economy in the following manner: (1) by introducing a new class of agents – oligarchs – that represent leaders of firms in a common industry who lobby for beneficial subsidies through campaign donations; and (2) by investigating the effects of ideological preferences of the oligarchs on legislative action. We test hypotheses from the literature in political economics on the behavior of oligarchs and political parties as they interact, under conditions of imperfect information and bounded rationality. Our key results indicate that (1) oligarchs tend to donate less to political campaigns when the parties are more resistant to changing their policies, or when voters are more in-formed; and (2) if Oligarchs donate to parties based on a combination of ideological and profit motivations, Oligarchs will tend to donate at a lower equilibrium level, due to the influence of lost profits. We validate these outcomes via comparisons to real world polling data on changes in party support over time.

SeHoon Lee, Jeong Hee Hong, Jang Won Bae and Il-Chul Moon
Journal of Artificial Societies and Social Simulation 18 (2) 5

Kyeywords: Agent-Based Simulation, Discrete Event Model, Urban Design, Population Modeling, Urban Simulator
Abstract: To reduce overpopulation around Seoul, Korea, the government implemented a relocation policy of public officers by moving the government complex. This implies that there will be a negative impact on the suburban area that originally hosted the complex, but we do not know the magnitude of the impact. Therefore, this paper presents a micro-level estimation of the impact on the city commerce with an agent-based model. This model is calibrated by the micro-level population census data, the time-use data, and the geographic data. Agent behavior is formally specified to illustrate the daily activities of diverse population types, and particularly the model observes how many agents pass by commercial buildings of interest. With the described model, we performed a virtual experiment that examines the strengths of factors in negatively influencing the city commerce. After the experiment, we statistically validated the model with the survey data from the real world, which resulted in relatively high correlation between the real world and the simulations.

Jonathan Ozik, Nicholson Collier, Todd Combs, Charles M. Macal and Michael North
Journal of Artificial Societies and Social Simulation 18 (3) 11

Kyeywords: Agent-Based Modeling, Statecharts, Agent-Based Social Simulation, Repast Simphony, Software Engineering Processes
Abstract: Agent states and transitions between states are important abstractions in agent-based social simulation (ABSS). Although it is common to develop ad hoc implementations of state-based and transition-based agent behaviors, “best practice” software engineering processes provide transparent and formally grounded design notations that translate directly into working implementations. Statecharts are a software engineering design methodology and an explicit visual and logical representation of the states of system components and the transitions between those states. Used in ABSS, they can clarify a model’s logic and allow for efficient software engineering of complex state-based models. In addition to agent state and behavioral logic representation, visual statecharts can also be useful for monitoring agent status during a simulation, quickly conveying the underlying dynamics of complex models as a simulation evolves over time. Visual approaches include drag-and-drop editing capabilities for constructing state-based models of agent behaviors and conditions for agent state transitions. Repast Simphony is a widely used, open source, and freely accessible agent-based modeling toolkit. While it is possible for Repast Simphony users to create their own implementations of state-based agent behaviors and even create dynamic agent state visualizations, the effort involved in doing so is usually prohibitive. The new statecharts framework in Repast Simphony, a subset of Harel’s statecharts, introduces software engineering practices through the use of statecharts that directly translate visual representations of agent states and behaviors into software implementations. By integrating an agent statecharts framework into Repast Simphony, we have made it easier for users at all levels to take advantage of this important modeling paradigm. Through the visual programming that statecharts afford, users can effectively create the software underlying agents and agent-based models. This paper describes the development and use of the free and open source Repast Simphony statecharts capability for developing ABSS models.

Andrew Collins, Mikel Petty, Daniele Vernon-Bido and Solomon Sherfey
Journal of Artificial Societies and Social Simulation 18 (3) 12

Kyeywords: Agent-Based Modeling and Simulation, Standards, Standardization, Standards Development Organization, ODD, Simulation Methods
Abstract: Standards are as old as civilization itself and they are vital to human development. Standards touch almost every part of our lives, from the water we drink to the language used to write this article. A sign of a good standard is one that we do not notice. Good standards exist and so do processes and organizations to create and maintain them. As agent-based modeling and simulation matures as a methodology, a discussion of standards applicable to it becomes increasingly important. Descriptive standards for agent-based models, such as the Overview, Design concepts, and Details protocol and agent-based extensions to the Unified Modeling Language, have already begun to emerge. Software tools for implementing such models, such as Netlogo and Repast Simphony, are increasingly well-known and have the potential to become de facto standards among the wider scientific community for agent-based simulation. Based on the findings of a series of workshops that brought together experts throughout the modeling and simulation community, we argue that agent-based modeling and simulation is no different from the other emerging technical subjects in the sense that standards, both existing and new, may be applicable to it, and that the community should both adopt existing standards that are relevant and exploit the already existing standards processes and organizations to develop new ones.

Peer-Olaf Siebers and Paul Davidsson
Journal of Artificial Societies and Social Simulation 18 (3) 13

Kyeywords: Agent-Based Social Simulation, Software Engineering, Software Architectures, UML
Abstract: This special section on "Engineering Agent-Based Social Simulations" aims to represent the current state of the art in using Software Engineering (SE) methods in ABSS. It includes a mixture of theoretically oriented papers that describe frameworks, notations and methods adapted from SE and practice-oriented papers that demonstrate the application of SE methods in real world ABSS projects.

Sabrina Scherer, Maria Wimmer, Ulf Lotzmann, Scott Moss and Daniele Pinotti
Journal of Artificial Societies and Social Simulation 18 (3) 14

Kyeywords: Model-Driven Development, Agent-Based Policy Models, Annotation of Policy Models, Conceptual Models, Social Simulation Models, Provenance Information
Abstract: Agent-based policy modelling is an application of agent-based social simulation. In this contribution it is applied to strategic policy making in the public sector. Open government principles relevant in this domain demand solutions that trace the origins of modelling decisions from narrative texts (background documents and stakeholder scenarios) through the whole policy modelling process up to the simulation results. With the help of such traces, decisions made on the basis of such simulation results are more transparent and comprehensible. This paper presents a conceptual model-driven approach developed and implemented in the OCOPOMO project. The approach ensures traceability by integrating technologies for agent-based social simulation, semantic web and model-driven development. Narrative texts are transferred into Consistent Conceptual Description (CCD) models. Those CCD models are transferred semi-automatically into formal policy models implemented in the DRAMS (Declarative Rule-based Agent Modelling System) language. These formal policy models are further elaborated (i.e. the policy modeller has still full flexibility in programming the model), and runnable simulation models are programmed. From the simulation logs, model-based scenarios are generated to interpret and support a better understanding of simulation results. The model-based scenarios are textual narratives with charts summarising the output produced by the simulation runs. Thereby passages in these texts are linked with documents containing original narrative scenarios. These traces are realised via the CCD models. A well-elaborated policy modelling process and a software toolbox support the approach. A pilot case exemplifies the application of the process and the toolbox. Evaluation results from the OCOPOMO project show benefits as well as limitations of the approach. We also reflect how the process and toolbox can be transferred into other application domains.

Johan Barthelemy and Philippe Toint
Journal of Artificial Societies and Social Simulation 18 (3) 15

Kyeywords: Micro-Simulation, Activity Chains, Transport Demand Forecasting, Nationwide Model, Large Population Simulation, Non Geo-Localized Data
Abstract: The VirtualBelgium project aims at developing an understanding of the evolution of the Belgian population using agent-based simulations and considering various aspects of this evolution such as demographics, residential choices, activity patterns, mobility, etc. This simulation is based on a validated synthetic population consisting of approximately 10,000,000 individuals and 4,350,000 households located in the 589 municipalities of Belgium. The work presented in this paper focuses only on the mobility behaviour of such large populations and this is simulated using an activity-based approach in which the travel demand is derived from the activities performed by the individuals. The proposed model is distribution-based and requires only minimal information, but is designed to easily take advantage of any additional network-related data available. The proposed activity-based approach has been applied to the Belgian synthetic population. The quality of the agent behaviour is discussed using statistical criteria extracted from the literature and results show that VirtualBelgium produces satisfactory results.

Dehua Gao, Xiuquan Deng, Qiuhong Zhao, Hong Zhou and Bing Bai
Journal of Artificial Societies and Social Simulation 18 (3) 17

Kyeywords: Organizational Routines, Connections, Complex Networks, Multiple Actors, Individual Habits, Multi-Agent Based Simulation
Abstract: Organizational routines are collective phenomena involving multiple individual actors. They are crucial in helping to understand how organizations behave and change in a certain period. In this paper, by regarding the individual habits of multiple actors involved as fundamental building blocks, we consider organizational routines from an ‘emergence-based’ perspective. We emphasise the impacts of connections or network topologies among individual actors in the formation of organizational routines, and carry out a multi-agent based simulation analysis of organizational routines on complex networks. We consider some important factors such as inertia resulted from individual memories, component complexity of organizational tasks, turnover of individual actors, the impacts of both heterogeneity and improvisation of individual actors involved, and the dynamical properties of the network topologies within which individual actors are located. The results of our research show that network topologies among individual actors do determine the dynamic characteristics of organizational routines. Although the fact is that the mechanisms beneath this are also influenced by some main factors like the memory capacity of individual actors and the component complexity of organizational tasks that these individual actors should deal with repetitively, and that the total costs for the organization to bear during their implementation of organizational tasks are variant, the routine system on scale-free networks can always have a better performance, and obtain a much higher coherency and routinization level of collective behaviours, even in the case of turnover of individual actors. In addition, when individual actors involved are heterogeneous, the routine system on scale-free networks would also exhibit a strong anti-disturbance ability, no matter whether there are minor improvisations from these individual actors or not. Nevertheless, a large number of improvisations enable individual actors to act in some more individualistic manners, and destroy the routine system as a result.

Stuart Rossiter
Journal of Artificial Societies and Social Simulation 18 (3) 9

Kyeywords: Software-Engineering, Simulation-Toolkits,, Reference-Architecture, Best-Practice
Abstract: There are growing initiatives to apply software engineering (SE) best-practice to computational science, which includes simulation. One area where the simulation literature appears to be particularly light is in the overall structural design of simulations, and what architectures and features are valuable for what reasons. (Part of the problem is that parts of this knowledge are abstracted away in simulation toolkits which are often not easily comparable, and have different conceptual aims.) To address this, I outline three key software properties which embody SE best-practices, and then define an 'idealised' software architecture for simulation—what SE would call a reference architecture—which strongly exhibits them. I show that this is universal to all simulations (largely because modelling-paradigm-specific detail is encapsulated into a 'single black box' layer of functionality) but that simulation toolkits tend to differ in how they map to them; this relates to the aims of the toolkits, which I provide a useful categorisation of. I show that, interestingly, there are several core features of this architecture that are not fully represented in any simulation toolkit that I am aware of. I present a library—JSIT—which provides some proof-of-concept implementations of them for Java-based toolkits. This library, and other ideas in the reference architecture, are put into practice on a published, multi-paradigm model of health and social care which uses the AnyLogic toolkit. I conclude with some thoughts on why this area receives so little focus, how to take it forwards, and some of the related cultural issues.

Luis R. Izquierdo, Doina Olaru, Segismundo S. Izquierdo, Sharon Purchase and Geoffrey N. Soutar
Journal of Artificial Societies and Social Simulation 18 (4) 1

Kyeywords: Fuzzy Logic, NetLogo, Social Simulation, Agent-Based Modelling, Mamdani Inference, IF-THEN Rule
Abstract: Fuzzy Logic is a framework particularly useful to formalise and deal with imprecise concepts and statements expressed in natural language. This paper has three related aims. First, it aims to provide a short introduction to the basics of Fuzzy Logic within the context of social simulation. Secondly, it presents a well-documented NetLogo extension that facilitates the use of Fuzzy Logic within NetLogo. Finally, by providing a concrete example, it shows how researchers can use the Fuzzy Logic extension to build agent-based models in which individual agents hold their own fuzzy concepts and use their own fuzzy rules, which may also change over time. We argue that Fuzzy Logic and the tools provided here can be useful in Social Simulation in different ways. For example, they can assist in the process of analysing the robustness of a certain social theory expressed in natural language to different specifications of the imprecise concepts that the theory may contain (such as e.g. “wealthy”, “poor” or “disadvantaged”). They can also facilitate the exploration of the effect that heterogeneity in concept interpretations may have in a society (i.e. the significance of the fact that different people may have different interpretations of the same concept). Thus, this paper and the tools included in it can make the endeavour of translating social theories into computer programs easier and more rigorous at the same time.

Woo-Seop Yun, Il-Chul Moon and Tae-Eog Lee
Journal of Artificial Societies and Social Simulation 18 (4) 10

Kyeywords: Command and Control (C2), Combat Effectiveness, Infantry Company Engagement, Agent-Based Simulation
Abstract: Modelling command and control (C2) is regarded as a difficult task because of the complexity of the decision-making required by individuals in combat. Despite the difficulties, C2 modelling is frequently used for high echelon units, i.e. battalion, division and above. This paper extends these models to the lowest army unit: the infantry company. Previous studies have modelled this particular unit as either an abstract entity or a detailed behaviour model without C2. Our model includes C2 in the models to determine the most critical tasks at company level C2 because this information could direct company commanders to engage in more important operational tasks. Our analysis is based on agent-based modelling and the virtual experiment framework. The overall model includes operational details as discrete event models and soldier behaviour as behavioural models. Our analytical results enable us to identify the key C2 tasks of company commanders and the changes in the importance of various operational environments.

Nicholas Seltzer and Oleg Smirnov
Journal of Artificial Societies and Social Simulation 18 (4) 12

Kyeywords: Cooperation, Social Networks, Small-World, Modern Society, Simulation, Agent-Based
Abstract: We analyze a novel agent-based model of a social network in which agents make contributions to others conditional upon the social distance, which we measure in terms of the “degrees of separation” between the two players. On the basis of a simple imitation model, the emerging strategy profile is characterized by high levels of cooperation with those who are directly connected to the agent and lower but positive levels of cooperation with those who are indirectly connected to the agent. Increasing maximum interaction distance decreases cooperation with close neighbors but increases cooperation with distant neighbors for a net negative effect. On the other hand, allowing agents to learn and imitate socially distant neighbors increases cooperation for all types of interaction. Combining greater interaction distance with greater learning distance leads to a positive change in the total social welfare produced by the agents’ contributions.

Simon Angus and Behrooz Hassani-Mahmooei
Journal of Artificial Societies and Social Simulation 18 (4) 16

Kyeywords: Agent Based Modelling, Social Sciences, Simulation, Publishing
Abstract: Agent Based Modelling (ABM), a promising scientific toolset, has received criticism from some, in part, due to a claimed lack of scientific rigour, especially in the communication of its methods and results. To test the veracity of these claims, we conduct a structured analysis of over 900 scientific objects (figures, tables, or equations) that arose from 128 ABM papers published in the Journal of Artificial Societies and Social Simulation (JASSS), during the period 2001 to 2012 inclusive. Regrettably, we find considerable evidence in support of the detractors of ABM as a scientific enterprise: elementary plotting attributes are left off more often than not; basic information such as the number of replicates or the basis behind a particular statistic are not included; and few, if any, established methodological communication standards are apparent. In short, 'anarchy reigns'. Whilst the study was confined only to ABM papers of JASSS, we conclude that if the ABM community wishes its approach to be accepted further afield, authors, reviewers, and editors should take the results of our work as a wake-up call.

Petra Ahrweiler, Michel Schilperoord, Andreas Pyka and Nigel Gilbert
Journal of Artificial Societies and Social Simulation 18 (4) 5

Kyeywords: Research Networks, Policy Modelling, Simulation Laboratory, EU Research Landscape
Abstract: This paper presents the agent-based model INFSO-SKIN, which provides ex-ante evaluation of possible funding policies in Horizon 2020 for the European Commission’s DG Information Society and Media (DG INFSO). Informed by a large dataset recording the details of funded projects, the simulation model is set up to reproduce and assess the funding strategies, the funded organisations and projects, and the resulting network structures of the Commission’s Framework 7 (FP7) programme. To address the evaluative questions of DG INFSO, this model, extrapolated into the future without any policy changes, is taken as an evidence-based benchmark for further experiments. Against this baseline scenario the following example policy changes are tested: (i) What if there were changes to the thematic scope of the programme? (ii) What if there were changes to the instruments of funding? (iii) What if there were changes to the overall amount of programme funding? (iv) What if there were changes to increase Small and Medium Enterprise (SME) participation? The results of these simulation experiments reveal some likely scenarios as policy options for Horizon 2020. The paper thus demonstrates that realistic modelling with a close data-to-model link can directly provide policy advice.

L. Andrew Bollinger, Martti J. van Blijswijk, Gerard P.J. Dijkema and Igor Nikolic
Journal of Artificial Societies and Social Simulation 19 (1) 1

Kyeywords: Socio-Technical Systems, Electricity Systems, Modelling Tools, Social Simulation, Netlogo, Matpower
Abstract: The growing importance of links between the social and technical dimensions of the electricity infrastructure mean that many research problems cannot be effectively addressed without joint consideration of social and technical dynamics. This paper motivates the need for and introduces a tool to facilitate the development of linked social and technical models of electric power systems. The tool, called MatpowerConnect, enables the runtime linkage of Netlogo - an oft-used modelling platform in the social simulation domain - with Matpower - a common power flow simulation package in the power systems domain. MatpowerConnect opens up new modelling possibilities for social simulation researchers active in the study of electricity systems. It offers ease of use coupled with a high degree of realism with which electricity infrastructure functionality is captured. We describe the development and use of two demonstration models using MatpowerConnect. These models illustrate two types of problems and system scales that can be addressed. In the first model we explore the consequences of actors' adaptive strategies on the performance of a small-scale power system. In the second model we simulate the effects of different regulatory regimes on network investment in a supra-national electricity transmission system to explore the long-term consequences for network development and social welfare. In both cases, the extension enables capturing a critical functionality of electric power systems, while allowing model development efforts to focus on social simulation aspects. Resources for using the extension are provided in conjunction with this paper.

Juliette Rouchier and Emily Tanimura
Journal of Artificial Societies and Social Simulation 19 (2) 7

Kyeywords: Collective Learning, Agent-Based Simulation, M2M, Influence Model, Analytical Model, Over-Confidence
Abstract: In this paper, we describe a process of validation for an already published model, which relies on the M2M paradigm of work. The initial model showed that over-confident agents, which refuse to communicate with agents whose beliefs differ, disturb collective learning within a population. We produce an analytical model based on probabilistic analysis, that enables us to explain better the process at stake in our first model, and demonstrates that this process is indeed converging. To make sure that the convergence time is meaningful for our question (not just for an infinite number of agents living for an infinite time), we use the analytical model to produce very simple simulations and assess that the result holds in finite contexts.

Viktoria Spaiser and David J. T. Sumpter
Journal of Artificial Societies and Social Simulation 19 (3) 1

Kyeywords: Agent-Based Simulation, Human Development Sequence Theory, Democratisation, Mathematical Modeling, Data Analysis, Inequality
Abstract: Agent-based models and computer simulations are promising tools for studying emergent macro-phenomena. We apply an agent-based approach in combination with data analysis to investigate the human development sequence (HDS) theory developed by Ronald Inglehart and Christian Welzel. Although the HDS theory is supported by correlational evidence, the sequence of economic growth, democracy and emancipation stated by the theory is not entirely consistent with data. We use an agent-based model to make quantitative predictions about several different micro-level mechanisms. Comparison to data allows us to identify important inconsistencies between HDS and the data, and propose revised agent-based models that modify the theory. Our results indicate the importance of elites and economic inequality in explaining the data available on democratisation.

Flávia Pereira dos Santos, Diana Adamatti, Henrique Rodrigues, Glenda Dimuro, Esteban De Manuel Jerez and Graçaliz Pereira Dimuro
Journal of Artificial Societies and Social Simulation 19 (3) 12

Kyeywords: Urban Ecosystem, Social Organization Simulation, Simulation of Social Production and Management Processes, Regulatory Policy Simulation, Multiagent-Based Simulations, JaCaMo Framework
Abstract: The concept of social production and management of urban ecosystems may be understood as the generation of new physical or relational situations, by constructing, transforming or eliminating physical and/or relational objects or ensuring the fulfillment of their social and environmental functions. This includes the citizen participation in the process of urban planning and transformation, forming a network structured and supported by tools allowing the equal distribution of power in the decision making. The SJVG-MAS Project addresses, in an interdisciplinary approach, the development of computational tools based on Multiagent Systems (MAS) for the simulation of the social production and management processes that occur in urban ecosystems, in particular, the San Jerónimo Vegetable Garden project (Spain). In this paper, we present a MAS-based simulation tool developed in JaCaMo. We conceived a 5-dimensional BDI-like agent social system composed of the agents' population, the social organization, the environment, the interactional/communication and the regulatory structures.

Stefan Holm, Renato Lemm, Oliver Thees and Lorenz M. Hilty
Journal of Artificial Societies and Social Simulation 19 (3) 3

Kyeywords: Agent-Based Modeling, Discrete Choice Experiments, Preference Elicitation, Decision Model, Market Simulation, Wood Market
Abstract: Agent-based modeling is a promising method to investigate market dynamics, as it allows modeling the behavior of all market participants individually. Integrating empirical data in the agents’ decision model can improve the validity of agent-based models (ABMs). We present an approach of using discrete choice experiments (DCEs) to enhance the empirical foundation of ABMs. The DCE method is based on random utility theory and therefore has the potential to enhance the ABM approach with a well-established economic theory. Our combined approach is applied to a case study of a roundwood market in Switzerland. We conducted DCEs with roundwood suppliers to quantitatively characterize the agents’ decision model. We evaluate our approach using a fitness measure and compare two DCE evaluation methods, latent class analysis and hierarchical Bayes. Additionally, we analyze the influence of the error term of the utility function on the simulation results and present a way to estimate its probability distribution.

Jan Drchal, Michal Čertický and Michal Jakob
Journal of Artificial Societies and Social Simulation 19 (3) 5

Kyeywords: Agent-Based Modelling, Activity Based Model, Transport, Validation, Methodology, Simulation
Abstract: Activity-based models are a specific type of agent-based models widely used in transport and urban planning to generate and study travel demand. They deal with agents that structure their behaviour in terms of daily activity schedules: sequences of activity instances (such as work, sleep or shopping) with assigned start times, durations and locations, and interconnected by trips with assigned transport modes and routes. Despite growing importance of activity-based models in transport modelling, there has been no work focusing specifically on statistical validation of such models so far. In this paper, we propose a six-step Validation Framework for Activity-based Models (VALFRAM) that exploits historical real-world data to quantify the model's validity in terms of a set of numeric metrics. The framework compares the temporal and spatial properties and the structure of modelled activity schedules against real-world origin-destination matrices and travel diaries. We demonstrate the usefulness of the framework on a set of six different activity-based transport models.

Christopher Poile and Frank Safayeni
Journal of Artificial Societies and Social Simulation 19 (3) 8

Kyeywords: Computational Modeling, Simulation, Theory-Building, Equifinality
Abstract: Computational modeling is a powerful method for building theory. However, to construct a computational model, researchers need to operationalize their cognitive or verbal theory into the specific terms demanded by the simulation’s language. This requires the researcher to make a series of reasonable assumptions to fill unanticipated “specificity gaps.” The problem is that many other reasonable assumptions could also have been made, and many of those resulting models would also match the conceptual theory. This is the problem of equifinality. We demonstrate the power and the dangers of computational modeling by building a simulation of a classic small group study. The results demonstrate that reasonable assumptions and equifinality are straightforward (but often overlooked) problems at the core of genuinely useful methodology. We offer recommendations and hope to open a dialog on other perspectives and solutions.

Haiming Liang, Yucheng Dong and Congcong Li
Journal of Artificial Societies and Social Simulation 19 (4) 1

Kyeywords: Opinion Formation, Uncertain Opinions, Uncertainty Tolerance, Communication Regime, Agent-Based Simulation
Abstract: Opinion formation describes the dynamics of opinions in a group of interaction agents and is a powerful tool for predicting the evolution and diffusion of the opinions. The existing opinion formation studies assume that the agents express their opinions by using the exact number, i.e., the exact opinions. However, when people express their opinions, sentiments, and support emotions regarding different issues, such as politics, products, and events, they often cannot provide the exact opinions but express uncertain opinions. Furthermore, due to the differences in culture backgrounds and characters of agents, people who encounter uncertain opinions often show different uncertainty tolerances. The goal of this study is to investigate the dynamics of uncertain opinion formation in the framework of bounded confidence. By taking different uncertain opinions and different uncertainty tolerances into account, we use an agent-based simulation to investigate the influences of uncertain opinions in opinion formation from two aspects: the ratios of the agents that express uncertain opinions and the widths of the uncertain opinions, and also provide the explanations of the observations obtained.

Nam Huynh, Johan Barthelemy and Pascal Perez
Journal of Artificial Societies and Social Simulation 19 (4) 11

Kyeywords: Synthetic Population, Combinatorial Optimisation, Sample-Free, Agent Based Modelling, Social Behaviours
Abstract: This paper presents an algorithm that follows the sample-free approach to synthesise a population for agent based modelling purposes. This algorithm is among the very few in the literature that do not rely on a sample survey data to construct a synthetic population, and thus enjoy a potentially wider applications where such survey data is not available or inaccessible. Different to existing sample-free algorithms, the population synthesis presented in this paper applies the heuristics to part of the allocation of synthetic individuals into synthetic households. As a result the iterative process allocating individuals into households, which normally is the most computationally demanding and time consuming process, is required only for a subset of synthetic individuals. The population synthesiser in this work is therefore computational efficient enough for practical application to build a large synthetic population (many millions) for many thousands target areas at the smallest possible geographical level. This capability ensures that the geographical heterogeneity of the resulting synthetic population is best preserved. The paper also presents the application of the new method to synthesise the population for New South Wales in Australia in 2006. The resulting total synthetic population has approximately 6 million people living in over 2.3 million households residing in private dwellings across over 11000 Census Collection Districts. Analyses show evidence that the synthetic population matches very well with the census data across seven demographics attributes that characterise the population at both household level and individual level.

Feiqiong Chen, Qiaoshuang Meng and Fei Li
Journal of Artificial Societies and Social Simulation 19 (4) 13

Kyeywords: Post-Merger Integration, Technology Innovation, Multi-Agent Simulation, Integration Degree, Target Autonomy
Abstract: The abilities to efficiently identify potential innovation profits and form an optimal post-merger strategy are key to evaluating overseas merger and acquisition (M&A) performances. The paper uses a global game with asymmetric payoff structure and multi-agent simulation methods to analyze the optimal overseas post-merger strategy. We model three stages of the M&A processes: merger decision stage, post-merger integration stage, and technology innovation after M&A, to analyze how different resource similarity and resource complementarity of the two companies influence the degree of optimal post-merger integration and target autonomy as well as technology innovation profit after M&A. The agent-based simulation shows that, in overseas M&As, resource similarity has a positive relation with integration and a negative relation with target autonomy; however, resource complementarity has the opposite effect. The negative interaction effect between resource similarity and complementarity will decrease the degrees of integration. In high-resource-similarity and low-resource-complementarity M&As, a high integration degree and low target autonomy will maximize innovation profit, while for high-resource-similarity and high-resource-complementarity M&As, a high integration degree and target autonomy is best for innovation profit. For low-resource-similarity and high-resource-complementarity M&As, a low integration degree and high target autonomy will be the best post-merger strategy. Model outputs are robust to variations of the parameters.

Thomas Farrenkopf, Michael Guckert, Neil Urquhart and Simon Wells
Journal of Artificial Societies and Social Simulation 19 (4) 14

Kyeywords: Social Simulation, Ontology, BDI Agent
Abstract: Within business games there is a need to provide realistic feedback for decisions made, if such business games are to continue to remain relevant in increasingly complex business environments. We address this problem by using software agents to simulate individuals and to model their actions in response to business decisions. In our initial studies we have used software agents to simulate consumers who make buying decisions based on their private preferences and those prevalent within their social network. This approach can be applied to search for behavioural patterns in social structures and to verify predicted values based on a priori theoretical considerations. Individual behaviour can be modelled for each agent and its effects within the marketplace can be examined by running simulations. Our simulations are founded upon the BDI software model (belief-desire-intention) combined with ontologies to make world knowledge available to the agents which can then determine their actions in accordance with this knowledge. We demonstrate how ontologies can be integrated into the BDI concept utilising the Jadex agent framework. Our examples are based upon the simulation of market mechanisms within the context of different industries. We use a framework, developed previously, known as AGADE within which each agent evolves its knowledge using an ontology maintained during the simulation. This generic approach allows the simulation of various consumer scenarios which can be modelled by creating appropriate ontologies.

Kei-Leo Brousmiche, Jean-Daniel Kant, Nicolas Sabouret and François Prenot-Guinard
Journal of Artificial Societies and Social Simulation 19 (4) 2

Kyeywords: Social Simulation, Attitude Formation, Cognitive Modeling, Calibration Using Field Data
Abstract: Attitude is a key concept in social psychology. The paper presents a novel agent-based model to simulate attitude formation by combining a rational and an emotional components based on cognitive, psychological and social theories. Individuals of the artificial population perceive actions taken by actors such as government or brands, they form an attitude toward them and also communicate the events through a social network. The model outputs are first studied through a functional analysis in which some unique macroscopic behaviors have emerged such as the impact of social groups, the resistance of the population toward disinformation campaigns or the social pressure. We then applied our model on a real world scenario depicting the effort of French Forces in their stabilization operations in Kapisa (Afghanistan) between 2010 and 2012. We calibrated the model parameters based on this scenario and the results of opinion polls that were conducted in the area during the same period about the sentiment of the population toward the Forces. Our model was able to reproduce polls results with a global error under 3%. Based on these results, we show the different dynamics tendencies that emerged among the population by applying a non-supervised classification algorithm.

Fujio Toriumi, Hitoshi Yamamoto and Isamu Okada
Journal of Artificial Societies and Social Simulation 19 (4) 6

Kyeywords: Groupware, Agent-Based Simulation, Meta-Sanction Game, Public Good Games,
Abstract: Groupware is an effective form of media for knowledge sharing and active open communication. One remaining important issue is how to design groupware in which vast amounts of beneficial content are provided and active discussion is facilitated. The behavior of information in such a medium resembles public-goods games because users voluntarily post beneficial information that creates media values. Many studies on such games have shown the effects of rewards or punishments in promoting cooperative behavior. In this paper, we show what types of incentive systems of rewards and punishments promote and maintain effective information behaviors or cooperative regimes in actual groupware. Our agent-based simulation demonstrates that a meta-reward system in which rewarders can gain other benefits for their own reward actions will probably encourage cooperation. Counterintuitively, our simulation also demonstrates that a system that applies sanctioning functions does not necessarily promote cooperation. Interestingly, a first-order reward system without any second-order incentives impedes the formation of cooperative regimes, while this is not the case with first-order punishment systems without second-order incentives. These findings may elucidate how successful groupware operates.

Ross Gore, Saikou Diallo, Christopher Lynch and Jose Padilla
Journal of Artificial Societies and Social Simulation 20 (1) 4

Kyeywords: Metamodel, Agent-Based Simulation, Statistical Modeling, Predicates, Validation
Abstract: Metamodeling refers to modeling a model. There are two metamodeling approaches for ABMs: (1) top-down and (2) bottom-up. The top down approach enables users to decompose high-level mental models into behaviors and interactions of agents. In contrast, the bottom-up approach constructs a relatively small, simple model that approximates the structure and outcomes of a dataset gathered from the runs of an ABM. The bottom-up metamodel makes behavior of the ABM comprehensible and exploratory analyses feasible. For most users the construction of a bottom-up metamodel entails: (1) creating an experimental design, (2) running the simulation for all cases specified by the design, (3) collecting the inputs and output in a dataset and (4) applying first-order regression analysis to find a model that effectively estimates the output. Unfortunately, the sums of input variables employed by first-order regression analysis give the impression that one can compensate for one component of the system by improving some other component even if such substitution is inadequate or invalid. As a result the metamodel can be misleading. We address these deficiencies with an approach that: (1) automatically generates Boolean conditions that highlight when substitutions and tradeoffs among variables are valid and (2) augments the bottom-up metamodel with the conditions to improve validity and accuracy. We evaluate our approach using several established agent-based simulations.

Jonas Hauke, Iris Lorscheid and Matthias Meyer
Journal of Artificial Societies and Social Simulation 20 (1) 5

Kyeywords: Social Simulation, Lines of Research, Multidisciplinary, Citation Analysis, Co-Citation Analysis
Abstract: The research field of social simulation comprises many topics and research directions. A previous study about the early years indicated that the community has evolved into a differentiated discipline. This paper investigates the recent development of social simulation as reflected in Journal of Artificial Societies and Social Simulation (JASSS) publications from 2008 to 2014. By using citation analysis, we identify the most influential publications and study the characteristics of citations. Additionally, we analyze the development of the field with respect to research topics and their structure in a co-citation analysis. The citation characteristics support the continuing highly multidisciplinary character of JASSS. Prominently cited are methodological papers and books, standards, and NetLogo as the main simulation tool. With respect to the focus of this research, we observe continuity in topics such as opinion dynamics and the evolution of cooperation. While some topics disappeared such as learning, new subjects emerged such as marriage formation models and tools and platforms. Overall, one can observe a maturing inter- and multidisciplinary scientific community in which both methodological issues and specific social science topics are discussed and standards have emerged.

Annalisa Fabretti and Stefano Herzel
Journal of Artificial Societies and Social Simulation 20 (1) 7

Kyeywords: Incentives, Agent-Based Simulations, Market Instability, Price Convergence, Order Book Analysis
Abstract: We studied the influence of convex incentives, e.g. option-like compensations, on the behavior of financial markets. Such incentives, usually offered to portfolio managers, have been often considered a potential source of market instability. We built an agent-based model of a double-auction market where some of the agents are endowed with convex contracts. We show that these contracts encourage traders to buy more aggressively, increasing total demand and market prices. Our analysis suggests that financial markets with many managers with convex contracts are more likely to be more unstable and less efficient.

Johannes Zschache
Journal of Artificial Societies and Social Simulation 20 (3) 1

Kyeywords: Reinforcement Learning, Agent-Based Simulation, N-Way Coordination Game, Roth-Erev Model
Abstract: In line with previous research, the evolution of social conventions is explored by n-way coordination games. A convention is said to be established if decisions of all actors synchronise over time. In contrast to the earlier studies, an empirically well-grounded process of reinforcement learning is used as behavioural assumption. The model is called melioration learning. It is shown by agent-based simulations that melioration enables actors to establish a convention. Besides the payoffs of the coordination game, the network structure of interactions affects actors' ability to coordinate their choices and the speed of convergence. The results of melioration learning are compared to predictions of the Roth-Erev model.

Carole Adam and Benoit Gaudou
Journal of Artificial Societies and Social Simulation 20 (3) 12

Kyeywords: Human Behaviour Modelling, Agent-Based Social Simulation, Crisis Management
Abstract: This paper describes a model for raising the decision-makers' awareness of the real (irrational and subjective) behaviours of the population in crisis situations. We analyse residents' statements and police hearings gathered after Victoria Black Saturday bushfires in 2009 to deduce a model of human behaviour based on the distinction between objective (capabilities, danger) and subjective (confidence, risk aversion) attributes, and on individual motivations. We evaluate it against observed behaviour archetypes and statistics, and show its explicative value.

Elizabeth Hunter, Brian Mac Namee and John D. Kelleher
Journal of Artificial Societies and Social Simulation 20 (3) 2

Kyeywords: Agent-Based, Epidemiology, Infectious Disease, Simulation, Model, Taxonomy
Abstract: Agent-based simulation modelling has been used in many epidemiological studies on infectious diseases. However, because agent based modelling is a field without any clear protocol for developing simulations the researcher is given a high amount of flexibility. This flexibility has led to many different forms of agent-based epidemiological simulations. In this paper we review the existing literature on agent-based epidemiological simulation models. From our literature review we identify key similarities and differences in the exisiting simulations. We then use these similarities and differences to create a taxonomy of agent-based epidemiological models and show how the taxonomy can be used.

Christoph Merdes
Journal of Artificial Societies and Social Simulation 20 (3) 5

Kyeywords: Social Norms, Agent-Based Simulation, Social Influence, Pluralistic Ignorance
Abstract: Unpopular norms are a pervasive and puzzling phenomenon of the social world. They are norms that are established and maintained against the interest of their subjects, but without external coercion. Pluralistic ignorance has been suggested as a potential explanation of unpopular norms. What is currently lacking is a formal model of this process that can be meaningfully compared with empirically known properties of pluralistic ignorance. An agent-based model of a growing social network can reproduce the most significant qualitative features, viz a deviation of the perceived norm from the preference distribution and the dynamical lag of the former behind the latter. In addition, the model is extended with a central influence representing for example central media or a powerful political elite.

Valentina Y. Guleva, Klavdiya O. Bochenina, Maria V. Skvorcova and Alexander V. Boukhanovsky
Journal of Artificial Societies and Social Simulation 20 (4) 15

Kyeywords: Interbank Network, Emergent Behavior, Topology Formation, Temporal Network, Complex System, Simulation Tool
Abstract: The topology of the interbank market plays a crucial role during a crisis, affecting the spreading or absorption of financial shock. The structure of an interbank network changes in the process of its evolution because of the interbank interactions and the interactions between banks and customers. To simulate a temporal interbank network, it is necessary to set an initial state and an evolution law for the topology and system entities. Because of the complex interplay between the network topology and the bank states, the stability of a temporal interbank network is generally unpredictable, even if all parameters and rules of interactions are known. In this paper, we present a simulation tool for temporal interbank networks aimed at exploring the different drivers contributing to evolutionary dynamics of banking networks. We describe a general-simulation scheme for temporal interbank networks and incorporate the creation and rewiring of edges because of the counter-party choices with the deletion of nodes and edges in case of a bank default. An example of the implementation of the general scheme is also presented and include models of banks and customers, strategies of counter-party choice, and clearing algorithms. To perform a qualitative and quantitative study of the evolutionary process, the proposed simulation tool supports the calculation of different topological and stability metrics and visualization of network evolution. The experimental study demonstrates (i) an illustrative example of the application of the simulation tool for synthetic networks while varying the counter-party choice policies and parameters of nodes and edges, and (ii) an investigation of the computational complexity and scalability of the simulation scheme.

Pierpaolo Angelini, Giovanni Cerulli, Federico Cecconi, Maria-Augusta Miceli and Bianca Potì
Journal of Artificial Societies and Social Simulation 20 (4) 4

Kyeywords: R&D Policy, Networks, Complexity, Social Simulation
Abstract: This paper presents an agent-based micro-policy simulation model assessing public R&D policy effect when R&D and non-R&D performing companies are located within a network. We set out by illustrating the behavioural structure and the computational logic of the proposed model; then, we provide a simulation experiment where the pattern of the total level of R&D activated by a fixed amount of public support is analysed as function of companies’ network topology. More specifically, the suggested simulation experiment shows that a larger “hubness” of the network is more likely accompanied with a decreasing median of the aggregated total R&D performance of the system. Since the aggregated firm idiosyncratic R&D (i.e., the part of total R&D independent of spillovers) is slightly increasing, we conclude that positive cross-firm spillover effects - in the presence of a given amount of support - have a sizeable impact within less centralized networks, where fewer hubs emerge. This may question the common wisdom suggesting that larger R&D externality effects should be more likely to arise when few central champions receive a support.

Zhaogang Ding, Yucheng Dong, Haiming Liang and Francisco Chiclana
Journal of Artificial Societies and Social Simulation 20 (4) 6

Kyeywords: Opinion Dynamics, Asynchronism, Bounded Confidence, Agent-Based Simulation
Abstract: Nowadays, about half of the world population can receive information and exchange opinions in online environments (e.g. the Internet), while the other half do so offline (e.g. face to face). The speed at which information is received and opinions are exchanged in online environment is much faster than offline. To model this phenomenon, in this paper we consider online and offline as two subsystems in opinion dynamics and assume asynchronization when agents in these two subsystems update their opinions. We unfold that asynchronization has a strong impact on the steady-state time of the opinion dynamics, the opinion clusters and the interactions between online and offline subsystems. Furthermore, these effects are often enhanced the larger the size of the online subsystem is.

Alexander V. Mantzaris, Samuel R. Rein and Alexander D. Hopkins
Journal of Artificial Societies and Social Simulation 21 (1) 1

Kyeywords: Simulation, Eurovision Song Contest, Voting Blocs, Sampling Schemes, JuliaLang
Abstract: The Eurovision Song Contest (ESC) is an annual event which attracts millions of viewers. It is an interesting activity to examine since the participants of the competition represent a particular country's musical performance that will be awarded a set of scores from other participating countries based upon a quality assessment of a performance. There is a question of whether the countries will vote exclusively according to the artistic merit of the song, or if the vote will be a public signal of national support for another country. Since the competition aims to bring people together, any consistent biases in the awarding of scores would defeat the purpose of the celebration of expression and this has attracted researchers to investigate the supporting evidence for biases. This paper builds upon an approach which produces a set of random samples from an unbiased distribution of score allocation, and extends the methodology to use the full set of years of the competition's life span which has seen fundamental changes to the voting schemes adopted. By building up networks from statistically significant edge sets of vote allocations during a set of years, the results display a plausible network for the origins of the culture anchors for the preferences of the awarded votes. With 60 years of data, the results support the hypothesis of regional collusion and biases arising from proximity, culture and other irrelevant factors in regards to the music which that alone is intended to affect the judgment of the contest.

Davide Secchi and Stephen J. Cowley
Journal of Artificial Societies and Social Simulation 21 (1) 13

Kyeywords: Organizational Cognition, Distributed Cognition, E-Cognition, Impact Factor, Perceived Scientific Value, Social Organizing, Agent-Based Simulation Modeling
Abstract: This article offers an alternative perspective on organizational cognition based on e-cognition whereby appeal to systemic cognition replaces the traditional computational model of the mind that is still extremely popular in organizational research. It uses information processing, not to explore inner processes, but as the basis for pursuing organizational matters. To develop a theory of organizational cognition, the current work presents an agent-based simulation model based on the case of how individual perception of scientific value is affected by and affects organizational intelligence units' (e.g., research groups', departmental) framing of the notorious impact factor. Results show that organizational cognition cannot be described without an intermediate meso scale – called here social organizing – that both filters and enables the many kinds of socially enabled perception, action and behavior that are so characteristic of human cognition.

Engi Amin, Mohamed Abouelela and Amal Soliman
Journal of Artificial Societies and Social Simulation 21 (1) 3

Kyeywords: Agent-Based Simulation, Cooperation, Public Goods Game, Laboratory Experiment, Social Preferences
Abstract: This paper examines the role of heterogeneous agents in the study of voluntary contributions to public goods. A human-subject experiment was conducted to classify agent types and determine their effects on contribution levels. Data from the experiment was used to build and calibrate an agent-based simulation model. The simulations display how different compositions of agent preference types affect the contribution levels. Findings indicate that the heterogeneity of cooperative preferences is an important determinant of a population’s contribution pattern.

Frank M. A. Klingert and Matthias Meyer
Journal of Artificial Societies and Social Simulation 21 (1) 7

Kyeywords: Continuous Double Auction, Logarithmic Market Scoring Rule, Market Mechanisms, Multi-Agent Simulation, Prediction Markets, Simulation Validation
Abstract: Prediction markets are a promising instrument for drawing on the “wisdom of the crowds”. For instance, in a corporate context they have been used successfully to forecast sales or project risks by tapping into the heterogeneous information of decentralized actors in and outside of companies. Among the main market mechanisms implemented so far in prediction markets are (1) the continuous double auction and (2) the logarithmic market scoring rule. However, it is not fully understood how this choice affects crucial variables like prediction market accuracy or price variation. Our paper uses an experiment-based and micro validated simulation model to improve the understanding of the mechanism-related effects and to inform further laboratory experiments. The results underline the impact of mechanism selection. Due to the higher number of trades and the lower standard deviation of the price, the logarithmic market scoring rule seems to have a clear advantage at a first glance. This changes when the accuracy level, which is the most important criterion from a practical perspective, is used as an independent variable; the effects become less straightforward and depend on the environment and actors. Besides these contributions, this work provides an example of how experimental data can be used to validate agent strategies on the micro level using statistical methods.

Tamsin E. Lee
Journal of Artificial Societies and Social Simulation 21 (2) 10

Kyeywords: Agent-Based Modelling, Individual-Based Model, Protest Behaviour, Social Simulation, Netlogo
Abstract: More frequently protests are accompanied by an opposing group performing a counter protest. This phenomenon can increase tension such that police must try to keep the two groups separated. However, what is the best strategy for police? This paper uses a simple agent-based model to determine the best strategy for keeping the two groups separated. The 'thin blue line' varies in density (number of police), width and the keenness of police to approach protesters. Three different groups of protesters are modelled to mimic peaceful, average and volatile protests. In most cases, a few police forming a single-file 'thin blue line' separating the groups is very effective. However, when the protests are more volatile, it is more effective to have many police occupying a wide 'thin blue line', and police being keen to approach protesters. To the authors knowledge, this is the first paper to model protests and counter-protests.

Mathieu Bourgais, Patrick Taillandier, Laurent Vercouter and Carole Adam
Journal of Artificial Societies and Social Simulation 21 (2) 5

Kyeywords: Emotion, Social Simulation, Survey
Abstract: Emotions play a key role in human behavior. Being able to integrate them in models is thus a major issue to improve the believability of agent-based social simulations. However, even though these last years have seen the emergence of many emotional models usable for simulations, many modelers still tend to use simple ad hoc emotional models. To support this view, this article proposes a survey of the different practices of modelers in terms of implementations of emotional models. We then present different emotional architectures that already exist and that can be used by modelers. The main goal is to understand the way emotions are used today in social simulations, in order for the community to unify its uses of emotional agents.

Friederike Wall
Journal of Artificial Societies and Social Simulation 21 (2) 6

Kyeywords: Agent-Based Simulation, Complexity, Coordination, Emergence, Reinforcement Learning, Task Formation
Abstract: This paper studies the emergence of task formation under conditions of limited knowledge about the complexity of the problem to be solved by an organization. Task formation is a key issue in organizational theory and the emergence of task formation is of particular interest when the complexity of the overall problem to be solved is not known in advance, since, for example, an organization is newly founded or has gone through an external shock. The paper employs an agent-based simulation based on the framework of NK fitness landscapes and controls for different levels of task complexity and for different coordination modes. In the simulations, artificial organizations are observed while searching for higher levels of organizational performance by two intertwined adaptive processes: short-termed search for superior solutions to the organizations' task and, in mid term, learning-based adaptation of task formation. The results suggest that the emerging task formations vary with the complexity of the underlying problem and, thereby, the balance between units' scope of competence and the organizational capacity for problem-solving is affected. For decomposable problems, task formations emerge which reflect the nature of the underlying problem; for non-decomposable structures, task formations with a broader scope of units' competence emerge. Furthermore, results indicate that, particularly for non-decomposable problems, the coordination mode employed in an organization subtly interferes with the emergence of task formation.

Tanzhe Tang and Ke Zeng
Journal of Artificial Societies and Social Simulation 21 (2) 7

Kyeywords: Yardstick Competition, Gubernatorial Election, Electoral Simulation, Political Economy
Abstract: Yardstick Competition is a unique feature of gubernatorial elections and may have a paramount role in the development of democracy and local government’s performance. This paper investigates the behaviours of governors and voters in an evolutionary game of gubernatorial election by introducing the spatial simulation process where voters can make comparisons between the incumbent and neighboring politicians. Based on the model, we portray the evolutionary process and topologies of local governments’ performances in federal systems. In the baseline model, we find that the variance of governor candidates’ performances, as well as the intensity of the yardstick competition, are positively related to the overall performance of governments. To study the relationship between elections and foreign policies, we employ an evolutionary Public Good Game in which governors can affect the welfare of neighbours by determining whether to invest in cross-provincial constructions. In the extended simulations where governors and voters are assigned to various characters, we find that asymmetry between candidates’ potentials and voters’ perception increases the uncertainty of the electoral results, and selfless voters will lead to lower performances of governments.

Ahmed Laatabi, Nicolas Marilleau, Tri Nguyen-Huu, Hassan Hbid and Mohamed Ait Babram
Journal of Artificial Societies and Social Simulation 21 (2) 9

Kyeywords: Empirical Agent-Based Models, ODD Protocol, ODD+2D, Mapping, Data Analysis, Social Simulation
Abstract: The quantity of data and processes used in modeling projects has been dramatically increasing in recent years due to the progress in computation capability and to the popularity of new approaches such as open data. Modelers face an increasing difficulty in analyzing and modeling complex systems that consist of many heterogeneous entities. Adapting existing models is relevant to avoid dealing with the complexity of writing and studying a new model from scratch. ODD (Overview, Design concepts, Details) protocol has emerged as a solution to document Agent-Based Models (ABMs). It appears to be a convenient solution to address significant problems such as comprehension, replication, and dissemination. However, it lacks a standard that formalizes the use of data in empirical models. This paper tackles this issue by proposing a set of rules that outline the use of empirical data inside an ABM. We call this new protocol ODD+2D (ODD+Decision + Data). ODD+2D integrates a mapping diagram called DAMap (Data to Agent Mapping). This mapping model formalizes how data are processed and mapped to agent-based models. In this paper, we focus on the architecture of ODD+2D, and we illustrate it with a residential mobility model in Marrakesh.

Segismundo S. Izquierdo and Luis R. Izquierdo
Journal of Artificial Societies and Social Simulation 21 (3) 2

Kyeywords: Social Simulation, Decision Support Systems, Deductive Inference, Fuzzy Logic, Mamdani
Abstract: Fuzzy logic presents many potential applications for modelling and simulation. In particular, this paper analyses one of the most popular fuzzy logic techniques: Mamdani systems. Mamdani systems can look particularly appealing because they are designed to incorporate expert knowledge in the form of IF-THEN rules expressed in natural language. While this is an attractive feature for modelling and simulating social and other complex systems, its actual application presents important caveats. This paper studies the potential use of Mamdani systems to explore the logical consequences of a model based on IF-THEN rules via simulation. We show that in the best-case scenario a Mamdani system provides a function that complies with its generating set of IF-THEN rules, which is a different exercise from that of finding the relation or consequences implied by those rules. In general, the logical consequences of a set of rules cannot be captured by a single function. Furthermore, the consequences of an IF-THEN rule in a Mamdani system can be very different from the consequences of that same rule in a system governed by the most basic principles of logical deductive inference. Thus, care must be taken when applying this tool to study “the consequences” of a set of hypothesis. Previous analyses have typically focused on particular steps of the Mamdani process, while here we present a holistic assessment of this technique for (deductive) simulation purposes.

Oliver Reinhardt, Jason Hilton, Tom Warnke, Jakub Bijak and Adelinde M. Uhrmacher
Journal of Artificial Societies and Social Simulation 21 (3) 9

Kyeywords: Agent-Based Modeling, Demography, Simulation Experimentation, Meta-Modeling
Abstract: In the last decade, the uptake of agent-based modeling in demography and other population sciences has been slowly increasing. Still, in such areas, where traditional data-driven, statistical approaches prevail, the hypothesis-driven design of agent-based models leads to questioning the validity of these models. Consequently, suitable means to increase the confidence into models and simulation results are required. To that end, explicit, replicable simulation experiments play a central role in model design and validation. However, the analysis of more complex models implies executing various experiments, each of which combines various methods. To streamline these experimentation processes a flexible computational simulation environment is necessary. With a new binding between SESSL -- an internal domain-specific language for simulation experiments -- and ML3 -- a simulator for linked lives designed specifically for agent-based demographic models -- we cater for these objectives and provide a powerful simulation tool. The proposed approach can serve as a foundation for current efforts of employing advanced and statistical model analysis of agent-based demographic models, as part of a wider process of iterative model building. We demonstrate its potential in specifying and executing different experiments with a simple model of return migration and a more complex model of social care.

Loïs Vanhée and Frank Dignum
Journal of Artificial Societies and Social Simulation 21 (4) 11

Kyeywords: Cultures, Social Simulations, Agent-Based Modelling
Abstract: This paper presents a simulation model and derived from it a theory to explain how known cultural influences on individual decisions lead to collective phenomena. This simulation models the evolution of a business organization, replicating key micro-level cultural influences on individual decisions (such as allocating and accepting tasks) and subsequent macro-level collective cultural phenomena (such as robustness and sensitivity to environmental complexity). As a result, we derived a theory on how to relate the influence of culture from individual decisions to collective outcomes, based on this simulation. We also point out that cultures appear to be related to specific sets of abstract, coherent and recurrent interaction patterns between individuals.

Elizabeth Hunter, Brian Mac Namee and John D. Kelleher
Journal of Artificial Societies and Social Simulation 21 (4) 9

Kyeywords: Agent-Based, Socioeconomic Status, Infectious Disease, Simulation, Segregation, Model
Abstract: Socioeconomic status can have an important effect on health. In this paper we: (i) propose using house price data as a publicly available proxy for socioeconomic status to examine neighbourhood socioeconomic status at a more fine grained resolution than is available in Irish Central Statistics Office data; (ii) use a dissimilarity index to demonstrate and measure the existence of socioeconomic clustering at a neighbourhood level; (iii) demonstrate that using a standard ABM initialisation process based on CSO small area data results in ABMs systematically underestimating the socioeconomic clustering in Irish neighbourhoods; (iv) demonstrate that ABM models are better calibrated towards socioeconomic clustering after a segregation models has been run for a burn-in period after initial model setup; and (v) that running a socieconomic segregation model during the initiation of an ABM epidemiology model can have an effect on the outbreak patterns of the model. Our results support the use of segregation models as useful additions to the initiation process of ABM for epidemiology.

Bhagya N. Wickramasinghe
Journal of Artificial Societies and Social Simulation 22 (1) 5

Kyeywords: Agent Based Modelling, Synthetic Population Reconstruction, Heuristic Population Construction, Sample Free, Integrating Models, Iterative Proportional Fitting
Abstract: This work proposes a novel application independent heuristics specifying framework and a household structures construction process, for sample-free population synthesis. The framework decouples heuristics and the algorithm by defining a set of generic constructs to specify heuristics on relationships and household structures. The algorithm uses Iterative Proportional Fitting, Monte Carlo sampling and combinatorial optimisation to synthesise the population. Decoupled nature of the system allows it to be used in different applications relatively easily by changing the heuristics. We demonstrate that this is a robust technique capable of producing synthetic agent populations highly consistent to input data distributions using two case studies. Apart from contributing to synthetic population reconstruction, this work will form one of the building blocks for integrating independently developed models to build complex new agent based models.

Barbara Llacay and Gilbert Peffer
Journal of Artificial Societies and Social Simulation 22 (1) 6

Kyeywords: Agent-Based Simulation, Financial Markets, Financial Stability, Value-At-Risk, Countercyclical Regulation, Basel III
Abstract: The financial system is inherently procyclical, as it amplifies the course of economic cycles, and precisely one of the factors that has been suggested to exacerbate this procyclicality is the Basel regulation on capital requirements. After the recent credit crisis, international regulators have turned their eyes to countercyclical regulation as a solution to avoid similar episodes in the future. Countercyclical regulation aims at preventing excessive risk taking during booms to reduce the impact of losses suffered during recessions, for example increasing the capital requirements during the good times to improve the resilience of financial institutions at the downturn. The Basel Committee has already moved forward towards the adoption of countercyclical measures on a global scale: the Basel III Accord, published in December 2010, revises considerably the capital requirement rules to reduce their procyclicality. These new countercyclical measures will not be completely implemented until 2019, so their impact cannot be evaluated yet, and it is a crucial question whether they will be effective in reducing procyclicality and the appearance of crisis episodes such as the one experienced in 2007-08. For this reason, we present in this article an agent-based model aimed at analysing the effect of two countercyclical mechanisms introduced in Basel III: the countercyclical buffer and the stressed VaR. In particular, we focus on the impact of these mechanisms on the procyclicality induced by market risk requirements and, more specifically, by value-at-risk models, as it is a issue of crucial importance that has received scant attention in the modeling literature. The simulation results suggest that the adoption of both of these countercyclical measures improves market stability and reduces the emergence of crisis episodes.

Haijun Bao, Xiaohe Wu, Haowen Wang, Qiuxiang Li, Yi Peng and Shibao Lu
Journal of Artificial Societies and Social Simulation 22 (1) 7

Kyeywords: Conflict of Interests, Land Expropriation, Evolutionary Game, Multi-Agent Simulation, Farmers
Abstract: Expropriation of collectively-owned land has become an important realistic path for achieving urban development and new urbanization in China considering the shortage of state-owned land. During this process, farmers involved in land expropriation are often in conflict with one another because of the asymmetry of their interests. Such conflicts have a considerable effect on social harmony and stability. However, few studies have investigated such conflict of interests between farmers. Therefore, this research analyzed game behavior for the conflict of interests among farmers. A two-dimensional symmetric evolutionary game model and a multi-agent simulation experiment were used to explore the conflicts induced by the farmers’ different responses to land expropriation. This research finds that the changing strategy choices of farmers in the evolutionary game on collectively owned land expropriation are the main reasons for the occurrence of villager’ confrontations and “nail households”. Results provide targeted policy recommendations for local governments to promote cooperation among farmers, thereby enhancing social harmony. The findings also serve as references for other countries and regions in dealing with intra-conflict of interests in land expropriation.

Patrick Taillandier, Arnaud Grignard, Nicolas Marilleau, Damien Philippon, Quang-Nghi Huynh, Benoit Gaudou and Alexis Drogoul
Journal of Artificial Societies and Social Simulation 22 (2) 3

Kyeywords: Agent-Based Simulation, Participatory Modeling, Participatory Simulation, Serious Game
Abstract: In recent years, agent-based simulation has become an important tool to study complex systems. However, the models produced are rarely used for decision-making support because stakeholders are often not involved in the modeling and simulation processes. Indeed, if several tools dedicated to participatory modeling and simulation exist, they are limited to the design of simple - KISS - models, which limit their potential impact. In this article, we present the participatory tools integrated within the GAMA modeling and simulation platform. These tools, which take advantage of the GAMA platform concerning the definition of rich - KIDS - models, allows to build models graphically and develop distributed serious games in a simple way. Several application examples illustrate their use and potential.

Tuong Manh Vu, Christian Wagner and Peer-Olaf Siebers
Journal of Artificial Societies and Social Simulation 22 (2) 7

Kyeywords: Agent-Based Modelling and Simulation, Continuous-Time Public Goods Game, Software Engineering, Agent-Based Computational Economics, Object-Oriented Analysis and Design
Abstract: Public Goods Games (PGGs) are a standard experimental economic approach to studying cooperative behaviour. There are two types of games: discrete-time and continuous-time PGGs. While discrete-time PGGs (one-shot decisions about contributions to public goods) can be easily done as lab experiments, continuous-time PGGs (where participants can change contributions at any time) are much harder to realise within a lab environment. This is mainly because it is difficult to consider events happening in continuous time in lab experiments. Simulation offers an opportunity to support real-world lab experiments and is well suited to explore continuous-time PGGs. In this paper, we show how to apply our recently developed ABOOMS (Agent-Based Object-Oriented Modelling and Simulation) development framework to create models for simulation-supported continuous-time PGG studies. The ABOOMS framework utilizes Software Engineering techniques to support the development at the macro level (considering the overall study lifecycle) and at the micro level (considering individual steps related to simulation model development). Our case study shows that outputs from the simulation-supported continuous-time PGG generate dynamics that do not exist in discrete-time setting, highlighting the fact that it is important to study both, discrete and continuous-time PGGs.

Almoaid Owaidah, Doina Olaru, Mohammed Bennamoun, Ferdous Sohel and Nazim Khan
Journal of Artificial Societies and Social Simulation 22 (2) 9

Kyeywords: Hajj, Crowd Modelling, Crowd Simulation, Big/special Events, Mass Gathering
Abstract: The Hajj is an Islamic pilgrimage that involves four main holy sites in Makkah, Saudi Arabia. As the number of participants (pilgrims) attending these events has been increasing over the years, challenges have arisen: overcrowding at the sites resulting in congestion, pilgrims getting lost, stampedes, injuries and even deaths. Although Hajj management authorities have employed up-to-date facilities to manage the events (e.g., state-of-the-art infrastructure and communication technologies, CCTV monitoring, live crowd analysis, time scheduling, and large well-trained police forces and scouts), there is still overcrowding and “unexpected” problems that can occur at the events. These problems can be studied and mitigated by prior simulation, which allows for preparation and deployment of the most appropriate plans for crowd management at Hajj events. This paper presents a comprehensive survey of crowd modelling and simulation studies referring to Hajj.

Hung Khanh Nguyen, Raymond Chiong, Manuel Chica, Richard Middleton and Dung Thi Kim Pham
Journal of Artificial Societies and Social Simulation 22 (3) 1

Kyeywords: Agent-Based Modeling, Contract Farming, Agricultural Supply Chain, Computational Simulation
Abstract: In this paper, we use agent-based modeling (ABM) to study different obstacles to the expansion of contract rice farming in the context of Mekong Delta (MKD)'s rice supply chain. ABM is a bottom-up approach for modeling the dynamics of interactions among individuals and complex combinations of various factors (e.g., economic, social or environmental). Our agent-based contract farming model focuses on two critical components of contractual relationship, namely financial incentives and trust. We incorporate the actual recurrent fluctuations of spot market prices, which induce both contractor and farmer agents to renege on the agreement. The agent-based model is then used to predict emergent system-wide behaviors and compare counterfactual scenarios of different policies and initiatives on maintaining the contract rice farming scheme. Simulation results firstly show that a fully-equipped contractor who opportunistically exploits a relatively small proportion (less than 10%) of the contracted farmers in most instances can outperform spot market-based contractors in terms of average profit achieved for each crop. Secondly, a committed contractor who offers lower purchasing prices than the most typical rate can obtain better earnings per ton of rice as well as higher profit per crop. However, those contractors in both cases could not enlarge their contract farming scheme, since either farmers' trust toward them decreases gradually or their offers are unable to compete with the benefits from a competitor or the spot market. Thirdly, the results are also in agreement with the existing literature that the contract farming scheme is not a cost-effective method for buyers with limited rice processing capacity, which is a common situation among the contractors in the MKD region. These results yield significant insights into the difficulty in expanding the agricultural contracting program in the MKD's rice supply chain.

Martin Klein, Ulrich J. Frey and Matthias Reeg
Journal of Artificial Societies and Social Simulation 22 (4) 6

Kyeywords: Agent Based Modelling, Computational Economics, Energy Systems Analysis, Modelling Guidelines, Policy Modelling, Energy Scenarios
Abstract: This paper tries to show the various roles agent-based modeling and simulation (ABMS) can play in technology and policy assessment of energy systems. We examine the advantages of ABMS methods using three case studies of electricity market models as example (AMIRIS, EMLab-Generation and PowerACE). In particular, we argue why ABMS might serve as framework for many future energy system models that integrate many different algorithms. We then discuss practical and theoretical problems in the development, validation and assessment of energy-system-analytical ABMS and conclude with an outlook and recommendations for energy system modellers who consider incorporating ABMS into their modelling toolbox.

Volker Grimm, Steven F. Railsback, Christian E. Vincenot, Uta Berger, Cara Gallagher, Donald L. DeAngelis, Bruce Edmonds, Jiaqi Ge, Jarl Giske, Jürgen Groeneveld, Alice S.A. Johnston, Alexander Milles, Jacob Nabe-Nielsen, J. Gareth Polhill, Viktoriia Radchuk, Marie-Sophie Rohwäder, Richard A. Stillman, Jan C. Thiele and Daniel Ayllón
Journal of Artificial Societies and Social Simulation 23 (2) 7

Kyeywords: Agent-Based Model, Individual-Based Model, Best Practice, Simulation Model, Standardization, Documentation
Abstract: The Overview, Design concepts and Details (ODD) protocol for describing Individual- and Agent-Based Models (ABMs) is now widely accepted and used to document such models in journal articles. As a standardized document for providing a consistent, logical and readable account of the structure and dynamics of ABMs, some research groups also find it useful as a workflow for model design. Even so, there are still limitations to ODD that obstruct its more widespread adoption. Such limitations are discussed and addressed in this paper: the limited availability of guidance on how to use ODD; the length of ODD documents; limitations of ODD for highly complex models; lack of sufficient details of many ODDs to enable reimplementation without access to the model code; and the lack of provision for sections in the document structure covering model design rationale, the model’s underlying narrative, and the means by which the model’s fitness for purpose is evaluated. We document the steps we have taken to provide better guidance on: structuring complex ODDs and an ODD summary for inclusion in a journal article (with full details in supplementary material; Table 1); using ODD to point readers to relevant sections of the model code; update the document structure to include sections on model rationale and evaluation. We also further advocate the need for standard descriptions of simulation experiments and argue that ODD can in principle be used for any type of simulation model. Thereby ODD would provide a lingua franca for simulation modelling.

Tuong Manh Vu, Charlotte Probst, Alexandra Nielsen, Hao Bai, Petra S. Meier, Charlotte Buckley, Mark Strong, Alan Brennan and Robin Purhouse
Journal of Artificial Societies and Social Simulation 23 (3) 1

Kyeywords: Agent-Based Modelling, Social Simulation, Software Architecture, Analytical Sociology, Abductive Reasoning
Abstract: This paper introduces the MBSSM (Mechanism-Based Social Systems Modelling) software architecture that is designed for expressing mechanisms of social theories with individual behaviour components in a unified way and implementing these mechanisms in an agent-based simulation model. The MBSSM architecture is based on a middle-range theory approach most recently expounded by analytical sociology and is designed in the object-oriented programming paradigm with Unified Modelling Language diagrams. This paper presents two worked examples of using the architecture for modelling individual behaviour mechanisms that give rise to the dynamics of population-level alcohol use: a single-theory model of norm theory and a multi-theory model that combines norm theory with role theory. The MBSSM architecture provides a computational environment within which theories based on social mechanisms can be represented, compared, and integrated. The architecture plays a fundamental enabling role within a wider simulation model-based framework of abductive reasoning in which families of theories are tested for their ability to explain concrete social phenomena.

Marcin Czupryna, Michał Jakubczyk and Paweł Oleksy
Journal of Artificial Societies and Social Simulation 23 (3) 11

Kyeywords: Parallel Trading, Trading Systems, Price Formation, Wine Investment, Agent Based Modelling
Abstract: What drives the prices of fine wines is not easy to discern, in view of a multitude of confounding factors characterising the transactions across several markets. At the same time, understanding the quantitative relationships and mechanisms that determine the price level is important for policy making (e.g. predicting the outcomes of regulations) and methodological purposes (which elements to consider in modelling these markets). We examine the price formation of fine wines simultaneously across three markets: an automated electronic exchange (Liv-ex), intermediated auctions, and over-the-counter (OTC). We use a unique dataset consisting of 99,769 price data points for Premier Cru Bordeaux fine wines and we examine the price determinants with Bayesian modelling. We ascertain the mean price ranking (OTC market being the most expensive and Liv-ex the least, differing by about 4.5% and -0.8% from the auctions). We also find a slight price decrease for larger transactions (approx.~0.3% reduction for a 10% volume increase) and some platykurtosis in price distribution (greatest in Liv-ex), and observe the most stochastic noise in auctions. In an agent-based simulation, we discover that it is necessary to include trading mechanisms, commissions, and OTC market heterogeneity to reproduce the observed characteristics. Our results indicate which elements should be included in future fine wine markets models.

Nicolas Malleson, Kevin Minors, Le-Minh Kieu, Jonathan Ward, Andrew West and Alison Heppenstall
Journal of Artificial Societies and Social Simulation 23 (3) 3

Kyeywords: Agent-Based Modelling, Particle Filter, Data Assimilation, Crowd Simulation, Pedestrian Modelling
Abstract: Agent-based modelling is a valuable approach for modelling systems whose behaviour is driven by the interactions between distinct entities, such as crowds of people. However, it faces a fundamental difficulty: there are no established mechanisms for dynamically incorporating real-time data into models. This limits simulations that are inherently dynamic, such as those of pedestrian movements, to scenario testing on historic patterns rather than real-time simulation of the present. This paper demonstrates how a particle filter could be used to incorporate data into an agent-based model of pedestrian movements at run time. The experiments show that although it is possible to use a particle filter to perform online (real time) model optimisation, the number of individual particles required (and hence the computational complexity) increases exponentially with the number of agents. Furthermore, the paper assumes a one-to-one mapping between observations and individual agents, which would not be the case in reality. Therefore this paper lays some of the fundamental groundwork and highlights the key challenges that need to be addressed for the real-time simulation of crowd movements to become a reality. Such success could have implications for the management of complex environments both nationally and internationally such as transportation hubs, hospitals, shopping centres, etc.

Masanori Hirano, Kiyoshi Izumi, Hiroyasu Matsushima and Hiroki Sakaji
Journal of Artificial Societies and Social Simulation 23 (3) 6

Kyeywords: Artificial Market, Multi-Agent Simulation, Data-Mining, High-Frequency Trade, Market-Making, Clustering
Abstract: Recently financial markets have shown significant risks and levels of volatility. Understanding the sources of these risks require simulation models capable of representing adequately the real mechanisms of markets. In this paper, we compared data of the high-frequency-trader market-making (HFT-MM) strategy from both the real financial market and our simulation. Regarding the former, we extracted trader clusters and identified one cluster whose statistical indexes indicated HFT-MM features. We then analyzed the difference between these traders' orders and the market price. In our simulation, we built an artificial market model with a continuous double auction system, stylized trader agents, and HFT-MM trader agents based on prior research. As an experiment, we compared the distribution of the order placements of HFT-MM traders in the real and simulated financial data. We found that the order placement distribution near the market or best price in both the real data and the simulations were similar. However, the orders far from the market or best price differed significantly when the real data exhibited a wider range of orders. This indicates that in order to build more realistic simulation of financial markets, integrating fine-grained data is essential.

Mathieu Bourgais, Patrick Taillandier and Laurent Vercouter
Journal of Artificial Societies and Social Simulation 23 (4) 12

Kyeywords: Social Simulation, Agent Architecture, BDI, Emotions, Personality, Emotional Contagion
Abstract: Over the last few years, the use of agent-based simulations to study social systems has spread to many domains (e.g., geography, ecology, sociology, economy). These simulations aim to reproduce real life situations involving human beings and thus need to integrate complex agents to match the behavior of the simulated people. Therefore, notions such as cognition, emotions, personality, social relationships or norms have to be taken into account, but there is currently no agent architecture that could incorporate all these features and be used by the majority of modelers, including those with low levels of skills in programming. In this paper, the BEN (Behavior with Emotions and Norms) architecture is introduced to tackle this issue. It is a modular architecture based on the BDI model of cognition and featuring modules to add emotions, emotional contagion, personality, social relationships and norms to agent behavior. This architecture is integrated into the GAMA simulation platform. An application of BEN to the simulation of the evacuation of a nightclub on fire is presented and shows the complexity of behaviors that may be developed with this architecture to create credible and expressive simulations.

Elizabeth Hunter, Brian Mac Namee and John Kelleher
Journal of Artificial Societies and Social Simulation 23 (4) 14

Kyeywords: Hybrid, Agent-Based, Equation Based, Infectious Disease, Simulation, Epidemiology
Abstract: Both agent-based models and equation-based models can be used to model the spread of an infectious disease. Equation-based models have been shown to capture the overall dynamics of a disease outbreak while agent-based models are able to capture heterogeneous characteristics of agents that drive the spread of an outbreak. However, agent-based models are computationally intensive. To capture the advantages of both the equation-based and agent-based models, we create a hybrid model where the disease component of the hybrid model switches between agent-based and equation-based. The switch is determined using the number of agents infected. We first test the model at the town level and then the county level investigating different switch values and geographic levels of switching. We find that a hybrid model is able to save time compared to a fully agent-based model without losing a significant amount of fidelity.

Markus Neumann
Journal of Artificial Societies and Social Simulation 23 (4) 2

Kyeywords: Altruism, Evolution, Network, Simulation, Small-World
Abstract: The question of why acts of selflessness occur in a Hobbesian self-help world has fascinated scholars for decades, if not centuries. Utilizing simulations, previous research has shown that altruism can be evolutionarily stable in small-scale societies under a narrow set of circumstances. However, when expanding such models to populations of anything larger than a few hundred people, they generally break down. In this paper, I modify the widely used image-score mechanism to include contagion-based reputation and demonstrate how altruism can survive in populations of up to 20,000. I also find that selflessness strongly depends on network topology - as heavily clustered small-world societies that resemble tight-knit family or friendship structures promote more cooperation than random networks where connections are more superficial.

Jean-Daniel Kant, Gérard Ballot and Olivier Goudet
Journal of Artificial Societies and Social Simulation 23 (4) 4

Kyeywords: Agent-Based Simulation, Dual Labor Markets, Anticipations, Bounded Rationality, Policy Evaluation
Abstract: In this paper, we provide an overview of the WorkSim model, an agent-based framework designed to study labor markets. The first objective of this model was to reproduce, within rigorous stock-flow accounting, the gross flows of individuals between important work-states: i.e., employment (distinguishing fixed term contracts and open-ended contracts), unemployment and inactivity. French legal institutions of the labor market are modelled in some detail and constrain the decisions of the agents on job flows and worker flows. Firms and individuals are heterogeneous and all decisions are taken on the basis of bounded rationality, yet employers as well as workers form imperfect anticipations. One important theoretical novelty of the model is that we consider multi-job firms and shocks on the individual demand of the firms. Employers consider anticipated shocks when they decide on the types of contract. Once the model was calibrated, the secondary objective was to characterize the nature of the labor market under study, and notably the differentiated roles of the two types of contracts and their impact on unemployment. This is achieved, first by examining the patterns of flows and stocks of labor and secondly by sensitivity experiments, modifying certain exogenous parameters and variables such as total demand. We then used the model as a tool for experimenting labor market policies, including changes in the labor law in France.

Christine Boshuijzen-van Burken, Ross Gore, Frank Dignum, Lamber Royakkers, Phillip Wozny and F. LeRon Shults
Journal of Artificial Societies and Social Simulation 23 (4) 6

Kyeywords: Agent Based Model, Value Sensitive Design, Simulation and Policy, Humanitarian Logistics, Refugees, Schwartz Values
Abstract: We have used value sensitive design as a method to develop an agent-based model of values in humanitarian logistics for refugees. Schwartz's theory of universal values is implemented in the model in such a way that agents can make value trade-offs, which are operationalized into a measure of refugee wellbeing and a measure of public opinion about how the refugee logistics is being handled. By trying out different ‘value-scenarios’, stakeholders who are responsible for, or involved in refugee logistics can have insights into the effects of various value choices. The model is visualized and made usable as a platform (interactive website) for decision-makers to understand the trade-offs in policies for government and non-government organizations.

Marco Cremonini and Samira Maghool
Journal of Artificial Societies and Social Simulation 23 (4) 8

Kyeywords: Stochastic Epidemic Model, Multi-Agent Simulation, Network Analysis, Agent-Based Model, Risk Analysis
Abstract: Lifting social restrictions is one of the most critical decisions that public health authorities have to face during a pandemic such as COVID-19. This work focuses on the risk associated with such a decision. We have called the period from the re-opening decision to epidemic expiration the ’final epidemic phase’, and considered the critical epidemic conditions which could possibly emerge in this phase. The factors we have considered include: the proportion of asymptomatic cases, a mitigation strategy based on testing and the average duration of infectious states. By assuming hypothetical configurations at the time of the re-opening decision and the partial knowledge concerning epidemic dynamics available to public health authorities, we have analyzed the risk of the re-opening decision based on possibly unreliable estimates. We have presented a discrete-time stochastic model with state-dependent transmission probabilities and multi-agent simulations. Our results show the different outcomes produced by different proportions of undetected asymptomatic cases, different probabilities of asymptomatic cases detected and contained, and a multivariate analysis of risk based on the average duration of asymptomatic and contained states. Finally, our analysis highlights that enduring uncertainty, typical of this pandemic, requires a risk analysis approach to complement epidemiological studies.

Toby Pilditch and Jens Koed Madsen
Journal of Artificial Societies and Social Simulation 24 (1) 5

Kyeywords: Micro-Targeted Campaigning, Cognitive Modelling, Source Credibility, Political Messaging, Simulation, Bayesian Modelling
Abstract: The use of data to inform and run political campaigning has become an inescapable trend in recent years. In attempting to persuade an electorate, micro-targeted campaigns (MTCs) have been employed to great effect through the use of tailored messaging and selective targeting. Here we investigate the capacity of MTCs to deal with the diversity of political preferences across an electorate. More precisely, via an Agent-Based Model we simulate various diverse electorates that encompass single issue, multiple issue, swing, and disengaged voters (among others, including combinations thereof) and determine the relative persuasive efficacy of MTCs when pitted against more traditional, population-targeting campaigns. Taking into account the perceived credibility of these campaigns, we find MTCs highly capable of handling greater voter complexity than shown in previous work, and yielding further advantages beyond traditional campaigns in their capacity to avoid inefficient (or even backfiring) interactions – even when fielding a low credibility candidate.

Daniele Vernon-Bido and Andrew Collins
Journal of Artificial Societies and Social Simulation 24 (1) 6

Kyeywords: Agent-Based Modeling, Cooperative Game Theory, Modeling and Simulation, ABM, Cooperative Games
Abstract: Agent-based modeling (ABM) is a powerful paradigm to gain insight into social phenomena. One area that ABM has rarely been applied is coalition formation. Traditionally, coalition formation is modelled using cooperative game theory. In this paper, a heuristic algorithm, which can be embedded into an ABM to allow the agents to find a coalition, is described. Our heuristic algorithm combines agent-based modeling and cooperative game theory to help find agent partitions that are members of a games' core solutions (if they exist). The accuracy of our heuristic algorithm can be determined by comparing its outcomes to the actual core solutions. This comparison is achieved by developing an experiment that uses a specific example of a cooperative game called the glove game. The glove game is a type of market economy game. Finding the traditional cooperative game solutions is computationally intensive for large numbers of players because each possible partition must be compared to each possible coalition to determine the core set; hence our experiment only considers up to nine-player games. The results indicate that our heuristic approach achieves a core solution over 90% of the games considered in our experiment.

Lucas Sage and Andreas Flache
Journal of Artificial Societies and Social Simulation 24 (2) 2

Kyeywords: Agent-Based Model, Social Simulation, Segregation, School-Segregation, School-Choice, Discrete-Choice-Model
Abstract: Schelling and Sakoda prominently proposed computational models suggesting that strong ethnic residential segregation can be the unintended outcome of a self-reinforcing dynamic driven by choices of individuals with rather tolerant ethnic preferences. There are only few attempts to apply this view to school choice, another important arena in which ethnic segregation occurs. In the current paper, we explore with an agent-based theoretical model similar to those proposed for residential segregation, how ethnic tolerance among parents can affect the level of school segregation. More specifically, we ask whether and under which conditions school segregation could be reduced if more parents hold tolerant ethnic preferences. We move beyond earlier models of school segregation in three ways. First, we model individual school choices using a random utility discrete choice approach. Second, we vary the pattern of ethnic segregation in the residential context of school choices systematically, comparing residential maps in which segregation is unrelated to parents’ level of tolerance to residential maps reflecting their ethnic preferences. Third, we introduce heterogeneity in tolerance levels among parents belonging to the same group. Our simulation experiments suggest that ethnic school segregation can be a very robust phenomenon, occurring even when about half of the population prefers segregated to mixed schools. However, we also identify a “sweet spot” in the parameter space in which a larger proportion of tolerant parents makes the biggest difference. This is the case when parents have moderate preferences for nearby schools and there is only little residential segregation. Further experimentation unraveled the underlying mechanisms.

Patrick Taillandier, Nicolas Salliou and Rallou Thomopoulos
Journal of Artificial Societies and Social Simulation 24 (2) 6

Kyeywords: Opinion Dynamics, Agent-Based Simulation, Argumentation Framework, Vegetarian Diets
Abstract: This paper introduces a generic agent-based model simulating the exchange and the diffusion of pro and con arguments. It is applied to the case of the diffusion of vegetarian diets in the context of a potential emergence of a second nutrition transition. To this day, agent-based simulation has been extensively used to study opinion dynamics. However, the vast majority of existing models have been limited to extremely abstract and simplified representations of the diffusion process. These simplifications impairs the realism of the simulations and disables the understanding of the reasons for the shift of an actor's opinion. The generic model presented here explicitly represents exchanges of arguments between actors in the context of an opinion dynamic model. In particular, the inner attitude towards an opinion of each agent is formalized as an argumentation graph and each agent can share arguments with other agents. Simulation experiments show that introducing attacks between arguments and a limitation of the number of arguments mobilized by agents has a strong impact on the evolution of the agents' opinion. We also highlight that when a new argument is introduced into the system, the quantity and the profile of the agents receiving the new argument will impact the evolution of the overall opinion. Finally, the application of this model to vegetarian diet adoption seems consistent with historical food behaviour dynamics observed during crises.

Lígia Mori Madeira, Bernardo Alves Furtado and Alan Dill
Journal of Artificial Societies and Social Simulation 24 (4) 1

Kyeywords: Domestic Violence, Violence Against Women, Agent-Based Models, Pandemics, Simulation, Metropolitan Regions
Abstract: Violence against women occurs predominantly in the family and domestic context. The COVID-19 pandemic has led Brazil to recommend and at times, impose social distancing, with the partial closure of economic activities, schools, and restrictions on events and public services. Preliminary evidence shows that intense coexistence increases domestic violence, while social distancing measures may have prevented access to public services and networks, information, and help. We propose an agent-based model (ABM), called VIDA, to formalize and illustrate a multitude of factors that influence events which could trigger violence. A central part of the model is the construction of a stress indicator, created as a probability trigger of domestic violence occurring within the family environment. Having a formal model that replicates observed patterns of violence based on internal familial characteristics enables us to experiment with altering dynamics. We first tested the (a) absence or presence of the deterrence system of domestic violence against women and then (b) the existence of measures to increase social distancing. VIDA presents comparative results for metropolitan regions and neighborhoods considered in the experiments. Results suggest that social distancing measures, particularly those encouraging staying at home, may have increased domestic violence against women by about 10%. VIDA suggests further that more populated areas have comparatively fewer cases per hundred thousand women than less populous capitals or rural areas of urban concentrations. This paper contributes to the literature by formalizing, to the best of our knowledge, the first model of domestic violence through agent-based modeling, using empirical detailed socioeconomic, demographic, educational, gender, and race data at the intraurban (census sectors) and household level.

Samuel Assefa, Aad Kessler and Luuk Fleskens
Journal of Artificial Societies and Social Simulation 24 (4) 8

Kyeywords: Social Simulation, Farmers, Soil and Water Conservation, Scenario Analysis, Ethiopia
Abstract: The sustainability of the ongoing Campaign-Based Watershed Management (CBWM) program in Ethiopia is questionable due to poor planning and implementation of the Soil and Water Conservation (SWC) structures. This study uses an empirically based, agent-based model to explore the effect of six scenarios on both area of land covered by, as well as the quality of SWC structures in three Kebeles (villages) of Boset District. The analysis revealed that integrating multiple interventions enhanced SWC most in all Kebeles. Furthermore, increasing the commitment of local government through capacity building generated most effect and yet required the lowest investment. Motivating farmers, introducing alternative livelihood opportunities and establishing and strengthening micro-watershed associations had limited, but differential influence on the outcomes across the Kebeles. However, all alternative scenarios had some added value compared to doing business as usual. Hence, in order to enhance the outcomes and sustainability of the ongoing CBWM program in the study area and other similar localities, it is crucial to pay much more attention to increasing the commitment of local government actors through capacity building. This empowers local government actors to (1) plan and more efficiently implement the program in consultation with other local actors, and (2) integrate locally sensitive need-based adaptation of the program.

Amir Hosein Afshar Sedigh, Martin Purvis, Tony Bastin Roy Savarimuthu, Christopher Konstantin Frantz and Maryam Purvis
Journal of Artificial Societies and Social Simulation 25 (1) 1

Kyeywords: Apprenticeship, Agent-Based Modelling, Social Simulations, Comparative Systems, Institutions, Historical Systems
Abstract: In this paper, we investigate the effects of different characteristics of apprenticeship programmes both in historical and contemporary societies. Apprenticeship is one of the major means to transfer skills in a society. We consider five societies: the Old Britain system (AD 1300s−1600s), the British East India Company (AD 1600s − 1800s), Armenian merchants of New-Julfa (AD 1600s − 1700s), contemporary German apprenticeship (1990s), and the “Modern Apprenticeship” in Britain (2001). In comparing these systems, using an agent-based simulation model, we identified six characteristics which impact the success of an apprenticeship programme in a society, which we measured by considering three parameters, namely the number of skilled agents produced by the apprenticeships, programme completion, and the contribution of programmes to the Gross Domestic Income (GDI) of the society. We investigate different definitions for success of an apprenticeship and some hypothetical societies to test some common beliefs about apprenticeships' performance. The simulations suggest that a) it is better to invest in a public educational system rather than subsidising private contractors to train apprentices, b) having a higher completion ratio for apprenticeship programme does not necessarily result in a higher contribution in the GDI, and c) governors (e.g. mayors or government) that face significant emigration should also consider employing policies that persuade apprentices to complete their programme and stay in the society after completion to improve apprenticeship efficacy.

Hendrik Nunner, Wojtek Przepiorka and Chris Janssen
Journal of Artificial Societies and Social Simulation 25 (1) 7

Kyeywords: Conventions, Repeated Games, Volunteer’s Dilemma, Agent-Based Simulation, Reinforcement Learning, Cognitive Modeling
Abstract: We use reinforcement learning models to investigate the role of cognitive mechanisms in the emergence of conventions in the repeated volunteer’s dilemma (VOD). The VOD is a multi-person, binary choice collective goods game in which the contribution of only one individual is necessary and sufficient to produce a benefit for the entire group. Behavioral experiments show that in the symmetric VOD, where all group members have the same costs of volunteering, a turn-taking convention emerges, whereas in the asymmetric VOD, where one “strong” group member has lower costs of volunteering, a solitary-volunteering convention emerges with the strong member volunteering most of the time. We compare three different classes of reinforcement learning models in their ability to replicate these empirical findings. Our results confirm that reinforcement learning models can provide a parsimonious account of how humans tacitly agree on one course of action when encountering each other repeatedly in the same interaction situation. We find that considering contextual clues (i.e., reward structures) for strategy design (i.e., sequences of actions) and strategy selection (i.e., favoring equal distribution of costs) facilitate coordination when optima are less salient. Furthermore, our models produce better fits with the empirical data when agents act myopically (favoring current over expected future rewards) and the rewards for adhering to conventions are not delayed.

Bernardo Alves Furtado
Journal of Artificial Societies and Social Simulation 25 (1) 8

Kyeywords: Public Policies, Real Estate Market, Agent-Based Modeling, Simulation, Spatial Analysis, Metropolitan Regions
Abstract: Policymakers' role in decision making on alternative policies is facing restricted budgets and an uncertain future. The need to decide on priorities and handle effects across policies has made their task even more difficult. For instance, housing policies involve heterogeneous characteristics of the properties themselves and the intricacy of housing markets within the spatial context of cities. Here, we have proposed PolicySpace2 (PS2) as an adapted and extended version of the open source PolicySpace agent-based model. PS2 is a computer simulation that relies on empirically detailed spatial data to model real estate, along with labor, credit, and goods and services markets. Interaction among workers, firms, a bank, households and municipalities follow the literature benchmarks by integrating economic, spatial and transport research. PS2 is applied here as a comparison of three competing public policies aimed at reducing inequality and alleviating poverty: (a) house acquisition by the government and distribution to lower income households, (b) rental vouchers and (c) monetary aid. Within the model context, monetary aid, that is smaller amounts of help for a larger number of households, improves the economy in terms of production, consumption, reduction of inequality and maintenance of financial duties. PS2 is also a framework that can be further adapted to a number of related research questions.

Kevin Chapuis, Patrick Taillandier and Alexis Drogoul
Journal of Artificial Societies and Social Simulation 25 (2) 6

Kyeywords: Synthetic Population, Agent-Based Simulation, Model Initialisation, Data-Driven Social Simulation
Abstract: To build realistic models of social systems, designers of agent-based models tend to incorporate a considerable amount of data, which influence the model outcomes. Data concerning the attributes of social agents, which compose synthetic populations, are particularly important but usually difficult to collect and therefore use in simulations. In this paper, we have reviewed state of the art methodologies and theories for building realistic synthetic populations for agent-based simulation models and practices in social simulations. We also highlight the discrepancies between theory and practice and outline the challenges in bridging this gap through a quantitative and narrative review of work published in JASSS between 2011 and 2021. Finally, we present several recommendations that could help modellers adopt best practices for synthetic population generation.

Tim G Williams, Daniel G Brown, Seth D Guikema, Tom M Logan, Nicholas R Magliocca, Birgit Müller and Cara E Steger
Journal of Artificial Societies and Social Simulation 25 (3) 1

Kyeywords: Agent-Based Model, Fairness, Justice, Reflexivity, Best Practice, Simulation
Abstract: Advancing equity is a complex challenge for society, science, and policy. Agent-based models are increasingly used as scientific tools to advance understanding of systems, inform decision-making, and share knowledge. Yet, equity has not received due attention within the agent-based modeling (ABM) literature. In this paper, we develop a conceptual framework and provide guidance for integrating equity considerations into ABM research and modeling practice. The framework conceptualizes ABM as interfacing with equity outcomes at two levels (the science-society interface and within the model itself) and the modeler as a filter and lens that projects knowledge between the target system and the model. Within the framework, we outline three complementary, equity-advancing action pathways: (1) engage stakeholders, (2) acknowledge positionality and bias, and (3) assess equity with agent-based models. For Pathway 1, we summarize existing guidance within the participatory modeling literature. For Pathway 2, we introduce the positionality and bias document as a tool to promote modeler and stakeholder reflexivity throughout the modeling process. For Pathway 3, we synthesize a typology of approaches for modeling equity and offer a set of preliminary suggestions for best practice. By engaging with these action pathways, modelers both reduce the risks of inadvertently perpetuating inequity and harness the opportunities for ABM to play a larger role in creating a more equitable future.

Daniele Baccega, Simone Pernice, Pietro Terna, Paolo Castagno, Giovenale Moirano, Lorenzo Richiardi, Matteo Sereno, Sergio Rabellino, Milena Maria Maule and Marco Beccuti
Journal of Artificial Societies and Social Simulation 25 (3) 2

Kyeywords: Agent-Based Simulation, SARS-CoV-2, Non-Pharmaceutical Interventions, Surveillance Testing, School
Abstract: Many governments enforced physical distancing measures during the COVID-19 pandemic to avoid the collapse of often fragile and overloaded health care systems. Following the physical distancing measures, school closures seemed unavoidable to keep the transmission of the pathogen under control, given the potentially high-risk of these environments. Nevertheless, closing schools was considered an extreme and the last resort of governments, and so various non-pharmaceutical interventions in schools were implemented to reduce the risk of transmission. By means of an agent-based model, we studied the efficacy of active surveillance strategies in the school environment. Simulations settings provided hypothetical although realistic scenarios which allowed us to identify the most suitable control strategy to avoid massive school closures while adapting to contagion dynamics. Reducing risk by means of public policies explored in our study is essential for both health authorities and school administrators.

Florian Kotthoff and Thomas Hamacher
Journal of Artificial Societies and Social Simulation 25 (3) 4

Kyeywords: Agent-Based Modeling, Multi-Agent Simulation, Innovation Diffusion, Adoption Model, Decision Making, Calibration
Abstract: Consumer behavior and the decision to adopt an innovation are governed by various motives, which models find difficult to represent. A promising way to introduce the required complexity into modeling approaches is to simulate all consumers individually within an agent-based model (ABM). However, ABMs are complex and introduce new challenges. Especially the calibration of empirical ABMs was identified as a key difficulty in many works. In this work, a general ABM for simulating the Diffusion of Innovations is described. The ABM is differentiable and can employ gradient-based calibration methods, enabling the simultaneous calibration of large numbers of free parameters in large-scale models. The ABM and calibration method are tested by fitting a simulation with 25 free parameters to the large data set of privately owned photovoltaic systems in Germany, where the model achieves a coefficient of determination of R² ≃ 0.7.

Tae-Sub Yun, Dongjun Kim, Il-Chul Moon and Jang Won Bae
Journal of Artificial Societies and Social Simulation 25 (4) 5

Kyeywords: Urban Traffic Simulation, Agent-Based Modeling, Traffic Dispersion Effect, Policy Analysis, Microscopic Analysis
Abstract: From the perspective of urban administration, simulation can be used as an evaluation tool. Specifically, it can provide an intuition to the current urban situation and quantitatively verify the effectiveness of urban policies. This study proposes a traffic simulation model for Sejong city in South Korea. The proposed model is developed as an agent-based model, which describes the movement behaviors of individual agents representing the whole population in the real city. In particular, to evaluate city-level administrative effects, the proposed model incorporates the multiple distributions of city reality by combining various types of observed real data. By aggregating the individual-level movement behaviors, the proposed model generates the demand for the city's transportation system, and the generated traffic demands were statistically validated with the real data. Based on the secured validity, we conducted a case study where the proposed model was used to compare and analyze the effect of traffic dispersion by taking the policy candidates of new bridge construction into account. From the policy experiment results, we discovered policy implications on an effective bridge construction. Furthermore, we found methodological implications of the urban transport model from the microscopic analysis, which is enabled by the virtue of the proposed model structure.

Vittorio Nespeca, Tina Comes and Frances Brazier
Journal of Artificial Societies and Social Simulation 26 (1) 10

Kyeywords: Research Design, Simulation Methodology, Empirical Agent-Based Models, Information Diffusion, Information Management, Crisis Management
Abstract: Qualitative research is a powerful means to capture human interactions and behavior. Although there are different methodologies to develop models based on qualitative research, a methodology is missing that enables to strike a balance between the comparability across cases provided by methodologies that rely on a common and context-independent framework and the flexibility to study any policy problem provided by methodologies that focus on capturing a case study without relying on a common framework. Additionally, a rigorous methodology is missing that enables the development of both theoretical and empirical models for supporting policy formulation and evaluation with respect to a specific policy problem. In this article, the authors propose a methodology targeting these gaps for ABMs in two stages. First, a novel conceptual framework centered on a particular policy problem is developed based on existing theories and qualitative insights from one or more case studies. Second, empirical or theoretical ABMs are developed based on the framework and generic models. This methodology is illustrated by an example application for disaster information management in Jakarta, resulting in an empirical descriptive agent-based model.

Ozge Dilaver and Nigel Gilbert
Journal of Artificial Societies and Social Simulation 26 (1) 4

Kyeywords: Transparency, Sensemaking, Model Structure, Model Description, Epistemology of Computer Simulation, Research Habitus
Abstract: This paper aims to improve the transparency of agent-based social simulation (ABSS) models and make it easier for various actors engaging with these models to make sense of them. It studies what ABSS is and juxtaposes its basic conceptual elements with insights from the agency/structure debate in social theory to propose a framework that captures the ‘conceptual anatomy’ of ABSS models in a simple and intuitive way. The five elements of the framework are: agency, social structure, environment, actions and interactions, and temporality. The paper also examines what is meant by the transparency or opacity of ABSS in the rapidly growing literature on the epistemology of computer simulations. It deconstructs the methodological criticism that ABSS models are black boxes by identifying multiple categories of transparency/opacity. It argues that neither opacity nor transparency is intrinsic to ABSS. Instead, they are dependent on research habitus - practices that are developed in a research field that are shaped by structure of the field and available resources. It discusses the ways in which thinking about the conceptual anatomy of ABSS can improve its transparency.

Rory Greig, Chris Major, Michalina Pacholska, Sebastian Bending and Jordi Arranz
Journal of Artificial Societies and Social Simulation 26 (2) 12

Kyeywords: Program Synthesis, Genetic Programming, Agent Based Modelling, Inverse Generative Social Science, Evolutionary Computing, Model Induction
Abstract: Genetic programming (GP) is a powerful method applicable to Inverse Generative Social Science (IGSS) for learning non-trivial agent logic in agent-based models (ABMs). While previous attempts at using evolutionary algorithms for learning ABM structures have focused on recombining domain-specific primitives, this paper extends prior work by developing techniques to evolve interpretable agent logic from scratch using a highly flexible domain-specific language (DSL) comprised of domain-independent primitives, such as basic mathematical operators. We demonstrate the flexibility of our method by learning symbolic models in two distinct domains: flocking and opinion dynamics, targeting data generated by reference models. Our results show that the evolved solutions closely resemble the reference models in behavior, generalize exceptionally well, and exhibit robustness to noise. Additionally, we provide an in-depth analysis of the generated code and intermediate behaviors, revealing the training process's progression. We explore techniques for further enhancing the interpretability of the resulting code and include a population-level analysis of the diversity for both models. This research demonstrates the potential of GP in IGSS for learning interpretable agent logic in ABMs across various domains.

Chathika Gunaratne, Erez Hatna, Joshua M. Epstein and Ivan Garibay
Journal of Artificial Societies and Social Simulation 26 (2) 7

Kyeywords: Agent-Based Modeling, Residential Segregation, Genetic Programing, Simulation, Complex Systems, Machine Learning
Abstract: The Schelling model of residential segregation has demonstrated that even the slightest preference for neighbors of the same race can be amplified into community-wide segregation. However, these models are unable to simulate mixed, coexisting patterns of segregation and integration, which have been seen to exist in cities. Using evolutionary model discovery we demonstrate how including social factors beyond racial bias when modeling relocation behavior enables the emergence of strongly mixed patterns. Our results indicate that the emergence of mixed patterns is better explained by multiple factors influencing the decision to relocate; the most important being the interaction of nonlinear, rapidly diminishing racial bias with a recent, historical tendency to move. Additionally, preference for less isolated neighborhoods or preference for neighborhoods with longer residing neighbors may produce weaker mixed patterns. This work highlights the importance of exploring the influence of multiple hypothesized factors of decision making, and their interactions, within agent rules, when studying emergent outcomes generated by agent-based models of complex social systems.

Nicolas Mauhe, Luis R. Izquierdo and Segismundo S. Izquierdo
Journal of Artificial Societies and Social Simulation 26 (2) 8

Kyeywords: Social Simulation, Computer Simulation, Refutation, Modelling, Counter-Example, Markov Chain
Abstract: This paper discusses a prominent way in which social simulations can contribute -and have contributed- to the advancement of Science, namely, by refuting some of our (wrong) beliefs about how the real world works. More precisely, social simulations can produce counter-examples that reveal something is wrong in a prevailing scientific assumption. In fact, in this paper we argue that this is a role that many well-known social simulation models in the literature have played and, arguably, it may be one of the main reasons why such well-known models became so popular. To test this hypothesis, in this paper we examine several popular models in the Social Simulation literature and indeed we find that all these models are most naturally interpreted as providers of compelling and reproducible (computer-generated) evidence that refuted some assumption or belief in a prevailing theory. By refuting prevailing theories, these models greatly advanced Science and, in some cases, they even opened up a new research field.

Carlos Andres Devia and Giulia Giordano
Journal of Artificial Societies and Social Simulation 26 (3) 1

Kyeywords: Agent-Based Social Simulation, Agent-Based Model, Opinion Formation, Opinion Dynamics, Real Data Validation
Abstract: We propose an agent-based opinion formation model characterised by a two-fold novelty. First, we realistically assume that each agent cannot measure the opinion of its neighbours about a given statement with infinite resolution and accuracy, and hence it can only perceive the opinion of others as agreeing much more, or more, or comparably, or less, or much less (than itself) with that given statement. This leads to a classification-based rule for opinion update. Second, we consider three complementary agent traits suggested by significant sociological and psychological research: conformism, radicalism and stubbornness. We rely on World Values Survey data to show that the proposed model has the potential to predict the evolution of opinions in real life: the classification-based approach and complementary agent traits produce rich collective behaviours, such as polarisation, consensus, and clustering, which can yield predicted opinions similar to survey results.

Yiyu Wang, Jiaqi Ge and Alexis Comber
Journal of Artificial Societies and Social Simulation 26 (3) 6

Kyeywords: Bayesian Nash Equilibrium, Pedestrian Modelling, Crowd Simulation, Game Theory, Agent-Based Simulations
Abstract: This research incorporates Bayesian game theory into pedestrian evacuation in an agent-based model. Three pedestrian behaviours were compared: Random Follow, Shortest Route and Bayesian Nash Equilibrium (BNE), as well as combinations of these. The results showed that BNE pedestrians were able to evacuate more quickly as they predict congestion levels in their next step and adjust their directions to avoid congestion, closely matching the behaviours of evacuating pedestrians in reality. A series of simulation experiments were conducted to evaluate whether and how BNE affects pedestrian evacuation procedures. The results showed that: 1) BNE has a large impact on reducing evacuation time; 2) BNE pedestrians displayed more intelligent and efficient evacuating behaviours; 3) As the proportion of BNE users rises, average evacuation time decreases, and average comfort level increases. A detailed description of the model and relevant experimental results is provided in this paper. Several limitations as well as further works are also identified.

Till Köster, Oliver Reinhardt, Martin Hinsch, Jakub Bijak and Adelinde M. Uhrmacher
Journal of Artificial Societies and Social Simulation 27 (1) 10

Kyeywords: Domain-Specific Language, Population-Based Models, Agent-Based Models, Continuous-Time Markov Chains, Simulation, Performance
Abstract: In agent-based simulation methods and applications, discrete timestep approaches prevail. To support continuous-time agent-based simulation, we analyze how methods for simulating population-based Con-tinu-ous-Time Markov Chains (CMTCs) can be adopted and derive implications for the concrete realization. To corroborate our findings, we develop an efficient internal domain-specific language (DSL) based on ML3, a modeling language for linked lives in demography. The design as an internal DSL, implemented within the Rust programming language, allows the modeler to exploit the complete feature set of the host language, such as data types and structures, when programming decision processes. A concise and expressive modeling of an agent's discrete decisions and behavior introducing exponentially distributed sojourn times can be supported by adapting the concept of guarded commands from population-based CTMCs. The execution of models relies on an optimized version of the direct method. This method is a variant of stochastic simulation algorithms, an established method for executing population-based CTMCs in other application areas, notably biochemistry. To efficiently handle the large set of possible transitions inherent to continuous-time agent-based models, we use a dependency graph whose updating scheme caters to the dynamic dependencies within agent-based models and the need for efficient implementation. The presented case studies include implementations of a continuous-time, agent-based migration model and a comparative performance study based on an extended SIR model of infection spread, allowing us to draw conclusions about the impact of different design choices on efficiency.

Andrew Collins, Matthew Koehler and Christopher Lynch
Journal of Artificial Societies and Social Simulation 27 (1) 11

Kyeywords: Agent-Based Modeling, Docking, Empirical Validation, Model Validation, Simulation Validation, Validation
Abstract: Validation is the process of determining if a model adequately represents the system under study for the model’s intended purpose. Validation is a critical component in building the credibility of a simulation model with its end-users. Effectively conducting validation can be a daunting task for both novice and experienced simulation developers. Further compounding the difficult task of conducting validation is that there is no universally accepted approach for assessing a simulation. These challenges are particularly relevant to the paradigm of Agent-Based Modeling and Simulation (ABMS) because of the complexity found in these models’ mechanisms and in the real-world situations they attempt to represent. To aid both the novice and expert in conducting a validation process for an agent-based simulation, this article reviews nine methods that are useful for this process, including foundational topics of docking, empirical validation, sampling, and visualization, as well as advanced topics of bootstrapping, causal analysis, inverse generative social science, and role-playing. Each method is reviewed with respect to its benefits and limitations as a validation-supporting method for ABMS. Suggestions that may support a validation plan for an agent-based simulations, are also provided. This article is an introductory guide for understanding and conducting ABMS validation for developers of all experience levels.

Marcin Czupryna, Katarzyna Growiec, Bogumił Kamiński and Paweł Oleksy
Journal of Artificial Societies and Social Simulation 27 (1) 2

Kyeywords: Schwartz Values, Economic Performance, Agent Based Modelling, Social Simulation
Abstract: In the literature, human values are defined as desirable, trans-situational goals serving as guiding principles in people's lives. Schwartz introduced the concept of ten different values that are grouped into four higher order values: openness to change, conservation, self-transcendence, and self-enhancement. Some of the Schwartz values will underlie acting for one's own good, the others for the good of the community. The collective output of the community will depend on these two types of actions and the relations between them. Acting for the benefit of others may, yet does not have to, increase the total benefit for the community, even when it leads to less benefit to the self. In this paper we provide an analogy for the mechanisms underlying the relation between Schwartz values and economic output. The observed economic output is a result of the behaviour of many heterogeneous agents interacting with each other. The main problem is to verify whether and how the differences in the distributions of Schwartz values in a given community may influence its collective economic output. We classify Schwartz values into two different groups, based on the different effects these values may have on the observed collective output. A higher importance of self-enhancement (power, achievement, and hedonism) and conservation (security, tradition, and conformity) increases working time in the public sector and the public goods return, while simultaneously lowering working time in the private sector and the private goods return. The values of openness to change (stimulation and self-direction) and self-transcendence (universalism and benevolence) have the opposite effect.

Alessia Antelmi, Pasquale Caramante, Gennaro Cordasco, Giuseppe D'Ambrosio, Daniele De Vinco, Francesco Foglia, Luca Postiglione and Carmine Spagnuolo
Journal of Artificial Societies and Social Simulation 27 (2) 4

Kyeywords: Agent-Based Model, Agent-Based Simulation Engine, Model Exploration and Optimization, Reliability and Efficiency, Open-Source
Abstract: Agent-based models represent a primary methodology to untangle and study complex systems. Over the last decade, the need for more elaborate computing-demanding models gave rise to many frameworks and tools to run ABM simulations. Current state-of-the-art ABM tools either focus on ease of use, performance, or a trade-off between these two elements. Still, efficiency-oriented solutions (required for both large and small-scale simulations) are vulnerable to memory flaws which could invalidate the experiment results. This work aims to merge efficiency, reliability, and safeness under an innovative ABM software framework based on the Rust programming language. Our framework, krABMaga, is an open-source library that offers a high-level environment by exploiting metaprogramming and expandable visualization features. We equipped our library with a dynamic simulation monitoring system and model exploration and optimization capabilities over parallel, distributed, and cloud architectures. After having presented the overall architecture and functionalities of krABMaga, we discuss a performance comparison of our framework against the mostly adopted ABM software and the scalability potential of our simulation engine on a model calibration experiment running over an AWS EC2 virtual cluster machine. All code and examples models are available on GitHub.

Sedar Olmez, Akhil Ahmed, Keith Kam, Zhe Feng and Alan Tua
Journal of Artificial Societies and Social Simulation 27 (2) 7

Kyeywords: Discrete-Event Simulation, Specialty Insurance Market, Lloyd, Individual-Based Model, Financial Markets, Underwriting Cycle
Abstract: This research presents a novel Discrete Event Simulation (DES) of the Lloyd's of London specialty insurance market, exploring complex market dynamics that have not been previously studied quantitatively. The proof-of-concept model allows for the simulation of various scenarios that capture important market phenomena such as the underwriting cycle, the impact of risk syndication, and the importance of appropriate exposure management. Despite minimal calibration, our model has shown that it is a valuable tool for understanding and analysing the Lloyd's of London specialty insurance market, particularly in terms of identifying areas for further investigation for regulators and participants of the market alike. The results generate the expected behaviours that, syndicates (insurers) are less likely to go insolvent if they adopt sophisticated exposure management practices, catastrophe events lead to more defined patterns of cyclicality and cause syndicates to substantially increase their premiums offered. Lastly, the syndication of risk via the lead and follow structure lead to less volatile and more coupled loss experiences among syndicates demonstrating that Lloyd's of London's regulatory market structure bolsters a healthier marketplace. Overall, this research offers a new perspective on the Lloyd's of London market and demonstrates the potential of individual-based modelling (IBM) for understanding complex financial systems.

Minyoung Choi and Jae-Suk Yang
Journal of Artificial Societies and Social Simulation 27 (3) 4

Kyeywords: Multi-Level Negotiation, Two-Level Game, Collaborative Decision-Making, Organizational Conflict Resolution, Simulation
Abstract: Organizational silos pose a common challenge for many companies, as they create barriers to communication, coordination, and resource efficiency. Addressing these challenges necessitates successful negotiation, yet the realm of multi-level team negotiation remains understudied. This research employs a computational simulation model to explore the dynamics of two-level negotiation, encompassing interactions of individuals searching for an agreement within and between teams in the organization. Our model involves individuals and teams with conflicting opinions on mutual interest issues. Within the intra-team negotiation process, the model integrates loyalty-driven opinion adjustments and the influence of the collective opinions of team members on team decisions. Concurrently, the inter-team negotiation introduces parameters reflecting teams’ willingness to negotiate with each other, emphasizing their openness to opinion adjustments. Our findings highlight the importance of individual loyalty, the leader acceptance ratio, and team willingness to negotiate as pivotal factors for achieving successful negotiation. We shed light on the mechanisms involved in two-level negotiations, including both within a team and between teams. This contribution enriches the literature on organizational negotiation and team dynamics in the context of organizational conflict. Moreover, this study advances the field by developing a computational simulation model, laying the groundwork for future studies exploring the multi-level negotiation processes. The insights in this study can equip managers with strategies to foster a win-win mindset for improved team coordination.

Catalina Canals, Spiro Maroulis, Alejandra Mizala, Enrique Canessa and Sergio Chaigneau
Journal of Artificial Societies and Social Simulation 27 (4) 2

Kyeywords: School Choice, Education, Public Policy, ABM, Computational Simulations
Abstract: Market-based reforms in education have expanded worldwide, often raising questions about their impact on the strength and sustainability of the public education sector. In this paper, we explore how such “school choice” policies affected public school enrollment in Chile, a country where a nationwide school choice reform coincided with a decline in public enrollment. To better understand the factors driving the public enrollment decline, we develop an agent-based model representing the education system in Chile between 2004 and 2016. We calibrate our model to data from four cities and conduct simulation experiments that disentangle the impacts of the hypothesized explanations for the decline. Our analysis reveals the importance of an institutional factor largely outside the core of the school choice policy – the grade-span configuration of schools in each sector. It also suggests that creating a formal coordination mechanism among primary and secondary public schools, to ensure students graduating from a primary public school a seat at a secondary public school, may be a promising policy for strengthening public enrollment. Other implications for understanding the decline in Chilean public enrollment are also discussed.

Jose Osvaldo Gonzalez-Hernandez, Jonathan Marino, Ted Rogers and Brandon Velasco
Journal of Artificial Societies and Social Simulation 27 (4) 3

Kyeywords: Expert Judgment, Forecast Scoring, Simulations
Abstract: We use Monte Carlo techniques to simulate an organized prediction competition between a group of a scientific experts acting under the influence of a ``self-governing'' prediction reward algorithm. Our aim is to illustrate the advantages of a specific type of reward distribution rule that is designed to address some of the limitations of traditional forecast scoring rules. The primary extension of this algorithm as compared with standard forecast scoring is that it incorporates measures of both group consensus and question relevance directly into the reward distribution algorithm. Our model of the prediction competition includes parameters that control both the level of bias from prior beliefs and the influence of the reward incentive. The Monte Carlo simulations demonstrate that, within the simplifying assumptions of the model, experts collectively approach belief in objectively true facts, so long as reward influence is high and the bias stays below a critical threshold. The purpose of this work is to motivate further research into prediction reward algorithms that combine standard forecasting measures with factors like bias and consensus.

Michael Belfrage, Emil Johansson, Fabian Lorig and Paul Davidsson
Journal of Artificial Societies and Social Simulation 27 (4) 4

Kyeywords: Policy-Modelling, Model Credibility, Accreditation, VV&A, Agent-Based Modelling & Simulation, ABM4Policy
Abstract: This paper explores the issue of model credibility of agent-based models and how it should be evaluated prior to application in policy-making. Specifically, the paper analyses related literature from different fields: (1) to establish a definition of model credibility – a measure of confidence in the model’s inferential capability – and (2) to assess how model credibility can be strengthened through Verification, Validation, and Accreditation (VV&A) prior to application and through post-application evaluation. Several studies have highlighted seriousshortcomings in how V&V of agent-based models is performed and documented, and few public administrations have an established model accreditation process. To address the first issue, we examine the literature on model V&V and, based on this review, introduce and outline the use of a V&V plan. To address the second issue, we draw inspiration from a practical use case of model accreditation applied by a government institution to propose a framework for the accreditation of agent-based models for policy-making. The paper concludes with a discussion of the risks associated with inappropriate assessments of model credibility.

Léo Biré, Quynh Nga Phung, Patrick Taillandier, Diep Anh Phung, Ngoc Doanh Nguyen and Alexis Drogoul
Journal of Artificial Societies and Social Simulation 28 (2) 4

Kyeywords: Serious Game, Agent-Based Simulation, Waste Management, Irrigation System, Red River Delta, Vietnam
Abstract: Waste management is a major issue in Vietnam, particularly in irrigation systems, where it has a profound impact on agriculture, which in turn also generates a significant amount of wastewater production. While irrigation users, residents and decision-makers are increasingly concerned about these issues, the implementation of collective solutions to these problems is almost non-existent. The challenge then is to propose a serious game that can open the dialogue on this issue, allowing stakeholders to envision shared and sustainable waste management solutions. To open the dialogue on waste management in rural areas in Vietnam, we propose RÁC (meaning “waste” in Vietnamese), an agent-based serious game using a concrete case study on waste management in the Bắc Hưng Hải irrigation system (Vietnam). RÁC places the stakeholders in the role of several village leaders who must ensure a sufficient level of agricultural production while minimizing both solid and wastewater pollution in order to maintain a quality label that is essential for selling agricultural products on the national market. The model was fully implemented using the open-source agent-based simulation platform GAMA. RÁC was used during four workshop sessions with farmers and village leaders in the Bắc Hưng Hải irrigation system. It allowed them to discuss and promote debate on waste management in their area, and to understand these stakeholders’ expectations on participatory approaches that focus on cohesion and emergence of leadership rather than on the will to express individual opinions. The results showed that the game was successful in helping players to discuss the issue of waste management. Future work in the short term will focus on continuing to organize game workshops in order to better assess the impact of the game on waste management coordination.

Jacob Borodovsky
Journal of Artificial Societies and Social Simulation 28 (2) 5

Kyeywords: Computation, Simulation, Epidemiology, Population, Substance Use, Complexity
Abstract: Background: “U-shaped” distributions of past 30-day substance use frequencies are pervasive, yet no established model explains this phenomenon. Using probability functions to describe these distributions yields unintuitive, atheoretical results. This study introduces a simple computational model of individual-level, longitudinal substance use patterns to understand how cross-sectional U-shaped distributions emerge in populations. Model: Each independent computational object transitions between two states: not using a substance (“N”), or using a substance (“U”). The model has two key components: (1) each object has a unique risk factor probability governing the transition from N to U, and a unique protective factor probability governing the transition from U to N; (2) an object’s current decision to use or not use is influenced by its prior decisions (i.e., “path dependence”). Three modeler input parameters control these two components. Analysis: First, the model is fit to empirical cross-sectional distributions of past 30-day use frequencies for ten substances (e.g., alcohol, cannabis, tobacco, etc.) from the U.S. National Survey on Drug Use and Health. Next, combinations of values of the model’s three inputs are tested to determine the conditions that produce U-shaped distributions. Finally, supplemental testing explored structural variations of the original model to assess whether simpler or alternative configurations are also capable of generating U-shaped distributions. Results: The model effectively reproduced the U-shaped distributions observed in empirical data across all substances. Path dependence emerged as a critical feature for generating U-shaped distributions, independent of the specific distribution shapes used for assigning transition probabilities. However, results also indicated that neither of the model's two key components are required for generating U-shaped distributions. Conclusion: This study demonstrates how a simple, theoretically-grounded computational model of individual-level substance use patterns can help substance use researchers understand the emergence of population-level, cross-sectional U-shaped distributions of substance use.