Ramzi Suleiman and Ilan Fischer
Journal of Artificial Societies and Social Simulation 3 (4) 1

Kyeywords: Prisoner's Dilemma, Intergroup Conflict, Evolution of Cooperation, Social Influence, Representation, Elections Frequency
Abstract: The study explores the evolution of decision strategies and the emergence of cooperation in simulated societies. In the context of an inter-group conflict, we simulate three different institutions for the aggregation of attitudes. We assume that: (a) the conflict can be modeled as an iterated Prisoner's Dilemma played by two decision makers, each representing her group for a fixed duration; (b) the performance of each group's representative influences her group members and, consequently, her prospects to be reelected. Our main objectives are: (1) to investigate the effects of three power-delegation mechanisms: Random Representation, Mean Representation, and Minimal Winning Coalition representation, on the emergence of representatives' decision strategies, (2) to investigate the effect of the frequency of elections on the evolving inter-group relations. Outcomes of 1080 simulations show that the emergence of cooperation is strongly influenced by the delegation mechanism, the election frequency, and the interaction between these two factors.

Bruce Edmonds
Journal of Artificial Societies and Social Simulation 9 (1) 10

Kyeywords: Evolution, Tags, Group, Symbiosis, Specialisation, Emergence
Abstract: This paper presents a evolutionary simulation where the presence of 'tags' and an inbuilt specialisation in terms of skills result in the development of 'symbiotic' sharing within groups of individuals with similar tags. It is shown that the greater the number of possible sharing occasions there are the higher the population that is able to be sustained using the same level of resources. The 'life-cycle' of a particular cluster of tag-groups is illustrated showing: the establishment of sharing; a focusing-in of the cluster; the exploitation of the group by a particular skill-group and the waning of the group. This simulation differs from other tag-based models in that is does not rely on either the forced donation of resources to individuals with the same tag and where the tolerance mechanism plays a significant part. These 'symbiotic' groups could provide the structure necessary for the true emergence of artificial societies, supporting a division of labour similar to that found in human societies.

Giangiacomo Bravo
Journal of Artificial Societies and Social Simulation 11 (1) 8

Kyeywords: Imitation, Evolution of Cooperation, Helping Game, Indirect Reciprocity
Abstract: The relation between imitation and cooperation in evolutionary settings presents complex aspects. From one hand, in any environment where egoists are favored over cooperators by selection processes, imitation should lead to a further spreading of the former ones due to the combined processes of individual selection and replication of successful behaviors. On the other hand, if cooperators succeed in forming clusters of mutual helping individuals, imitation may have a positive effect on cooperation by further reproducing this locally dominant behavior. This paper explores the relationship between imitation and cooperation by mean of a simulation model based on two different Helping games. Our model shows that different imitation mechanisms can favor the spreading of cooperation under a wide range of conditions. Moreover, the interplay of imitation and other factors — e.g. the possibility of performing “conditional associations” strategies — can further foster the success of cooperative agents.

Floriana Gargiulo and Alberto Mazzoni
Journal of Artificial Societies and Social Simulation 11 (4) 9

Kyeywords: Extremists, Segregation, Opinion Dynamics
Abstract: Many models have been proposed to explain the opinion formation in a group of individuals; most of these models study the opinion propagation as the interaction between nodes/agents in a social network. Opinion formation is a very complex process and a realistic model should also take into account the important feedbacks that the opinions of the agents have on the structure of the social networks and on the characteristics of the opinion dynamics. In this paper we will show that associating to different agents different kind of interconnections and different interacting behaviour can lead to interesting scenarios, like the co-existence of several opinion clusters, namely pluralism. In our model agents have opinions uniformly and continuously distributed between two extremes. The social network is formed through a social aggregation mechanism including the segregation process of the extremists that results in many real communities. We show how this process affects opinion dynamics in the whole society. In the opinion evolution we consider the different predisposition of single individuals to interact and to to modify each other's opinions; we associate to each individual a different tolerance threshold, depending on its own opinion: extremists are less willing to interact with individuals with strongly different opinions and to change significantly their ideas. A general result is obtained: when there is no interaction restriction, the opinion always converges to uniformity, but the same is happening whenever a strong segregation process of the extremists occurs. Only when extremists are forming clusters but these clusters keep interacting with the rest of the society, the survival of a wide opinion range is guaranteed.

Andrew Crooks, Andrew Hudson-Smith and Joel Dearden
Journal of Artificial Societies and Social Simulation 12 (4) 10

Kyeywords: Agent-Based Modelling, Pedestrian Evacuation, Segregation, Virtual Worlds, Second Life
Abstract: Urban models can be seen on a continuum between iconic and symbolic. Generally speaking, iconic models are physical versions of the real world at some scaled down representation, while symbolic models represent the system in terms of the way they function replacing the physical or material system by some logical and/or mathematical formulae. Traditionally iconic and symbolic models were distinct classes of model but due to the rise of digital computing the distinction between the two is becoming blurred, with symbolic models being embedded into iconic models. However, such models tend to be single user. This paper demonstrates how 3D symbolic models in the form of agent-based simulations can be embedded into iconic models using the multi-user virtual world of Second Life. Furthermore, the paper demonstrates Second Life\'s potential for social science simulation. To demonstrate this, we first introduce Second Life and provide two exemplar models; Conway\'s Game of Life, and Schelling\'s Segregation Model which highlight how symbolic models can be viewed in an iconic environment. We then present a simple pedestrian evacuation model which merges the iconic and symbolic together and extends the model to directly incorporate avatars and agents in the same environment illustrating how \'real\' participants can influence simulation outcomes. Such examples demonstrate the potential for creating highly visual, immersive, interactive agent-based models for social scientists in multi-user real time virtual worlds. The paper concludes with some final comments on problems with representing models in current virtual worlds and future avenues of research.

Jae-Woo Kim
Journal of Artificial Societies and Social Simulation 13 (3) 2

Kyeywords: Prisoner\'s Dilemma Game, Tags, Parochial Cooperation, Clustering, Small-World-Ness, NetLogo
Abstract: Researchers from many disciplines have been interested in the maintenance of cooperation in animal and human societies using the Prisoner\'s Dilemma game. Recent studies highlight the roles of cognitively simple agents in the evolution of cooperation who read tags to interact either discriminately or selectively with tolerably similar partners. In our study on a one-shot Prisoner\'s Dilemma game, artificial agents with tags and tolerance perceive dissimilarities to local neighbors to cooperate with in-group and otherwise defect. They imitate tags and learn tolerance from more successful neighbors. In terms of efficiency, society-wide cooperation can evolve even when the benefits of cooperation are relatively low. Meanwhile, tolerance however decreases as agents become homogenized. In terms of stability, parochial cooperators are gullible to the deviants defectors displaying tolerably similar tags. We find that as the benefits of cooperation increase and the dimensions of tag space become larger, emergent societies can be more tolerant towards heterogeneous others. We also identify the effects of clustering and small-world-ness on the dynamics of tag-based parochial cooperation in spite of its fundamental vulnerability to those deviants regardless of network topology. We discuss the issue of tag changeability in search for alternative societies in which tag-based parochial cooperation is not only efficient but also robust.

Jae-Woo Kim and Robert Hanneman
Journal of Artificial Societies and Social Simulation 14 (3) 1

Kyeywords: Workers Protest, Tags, Group Identity, Trust, Netlogo
Abstract: This paper presents an agent-based model of worker protest. Workers have varying degrees of grievance depending on the difference between their wage and the average of their neighbors. They protest with probabilities proportional to grievance, but are inhibited by the risk of being arrested – which is determined by the ratio of coercive agents to probable rebels in the local area. We explore the effect of similarity perception on the dynamics of collective behavior. If workers are surrounded by more in-group members, they are more risk-taking; if surrounded by more out-group members, more risk-averse. Individual interest and group membership jointly affect patterns of workers protest: rhythm, frequency, strength, and duration of protest outbreaks. Results indicate that when wages are more unequally distributed, the previous outburst tends to suppress the next one, protests occur more frequently, and they become more intensive and persistent. Group identification does not seriously influence the frequency of local uprisings. Both their strength and duration, however, are negatively affected by the ingroup-outgroup assessment. The overall findings are valid when workers distinguish \'us\' from \'them\' through simple binary categorization, as well as when they perceive degrees of similarity and difference from their neighbors.

Erez Hatna and Itzhak Benenson
Journal of Artificial Societies and Social Simulation 15 (1) 6

Kyeywords: Schelling Model, Ethnic Segregation, Minority-Majority Relations
Abstract: The Schelling model of segregation is an agent-based model that illustrates how individual tendencies regarding neighbors can lead to segregation. The model is especially useful for the study of residential segregation of ethnic groups where agents represent householders who relocate in the city. In the model, each agent belongs to one of two groups and aims to reside within a neighborhood where the fraction of 'friends' is sufficiently high: above a predefined tolerance threshold value F. It is known that depending on F, for groups of equal size, Schelling's residential pattern converges to either complete integration (a random-like pattern) or segregation. The study of high-resolution ethnic residential patterns of Israeli cities reveals that reality is more complicated than this simple integration-segregation dichotomy: some neighborhoods are ethnically homogeneous while others are populated by both groups in varying ratios. In this study, we explore whether the Schelling model can reproduce such patterns. We investigate the model's dynamics in terms of dependence on group-specific tolerance thresholds and on the ratio of the size of the two groups. We reveal new type of model pattern in which a portion of one group segregates while another portion remains integrated with the second group. We compare the characteristics of these new patterns to the pattern of real cities and discuss the differences.

Rainer Hegselmann
Journal of Artificial Societies and Social Simulation 15 (4) 9

Kyeywords: Schelling Model, Segregation, Configuration Game, History of Computational Social Science, Agent Based Modeling
Abstract: Today the Schelling model is a standard component in introductory courses to agent-based modelling and simulation. When Schelling presented his model in the years between 1969 and 1978, his own analysis was based on manual table top exercises. Even more, Schelling explicitly warned against using computers for the analysis of his model. That is puzzling. A resolution to that puzzle can be found in an essay that Schelling wrote as teaching material for his students. That essay is now published by Schelling in JASSS, exactly 40 years after it was written. In his essay, Schelling gives a guided tour of a computer implementation of his model he himself implemented, de-spite his warnings. On this tour, though more in passing, Schelling gives hints to an extremely generalised version of his model. My article explains why we find the gen-eralised version of Schelling's model on the tour through his computer program rather than in his published articles.

Alessio Emanuele Biondo, Alessandro Pluchino and Andrea Rapisarda
Journal of Artificial Societies and Social Simulation 16 (2) 11

Kyeywords: Brain Drain, Return Migration, Human Capital, Social Capital
Abstract: The Brain Drain phenomenon is particularly heterogeneous and is characterized by peculiar specifications. It influences the economic fundamentals of both the country of origin and the host one in terms of human capital accumulation. Here, the brain drain is considered from a microeconomic perspective: more precisely we focus on the individual rational decision to return, referring it to the social capital owned by the worker. The presented model compares utility levels to justify agent's migration conduct and to simulate several scenarios within a computational environment. In particular, we developed a simulation framework based on two fundamental individual features, i.e. risk aversion and initial expectation, which characterize the dynamics of different agents according to the evolution of their social contacts. Our main result is that, according to the value of risk aversion and initial expectation, the probability of return migration depends on their ratio, with a certain degree of approximation: when risk aversion is much bigger than the initial expectation, the probability of returns is maximal, while, in the opposite case, the probability for the agents to remain abroad is very high. In between, when the two values are comparable, it does exist a broad intertwined region where it is very difficult to draw any analytical forecast.

Yen-Sheng Chiang
Journal of Artificial Societies and Social Simulation 16 (2) 6

Kyeywords: Evolution of Cooperation, Complex Network, Spatial Game, Conditional Cooperation
Abstract: The investigation of how cooperation is achieved on graphs in the field of spatial game or network reciprocity has received proliferating attention in the biological and sociological literature. In line of the research, this paper provides an new account of how cooperation could evolve in complex networks when actors use information of network characteristics to strategize whether to cooperate or not. Different from past work that focuses exclusively on the evolution of unconditional cooperation, we are proposing new strategies that are choosy in whom to cooperate with, conditional on the structural attributes of the nodes occupied by actors. In a series of evolutionary tournaments conducted by computer simulation, the model shows that a pair of simple strategies-cooperating respectively with higher and lower nodal-attribute neighbors-can be advantageous in adaptive fitness when competing against unconditional cooperation and defection. In particular, these strategies of conditional cooperation work well in random graphs-a network known for being unfavorable to the selection of cooperation. This paper contributes to the literature by showing how network characteristics can serve as a mechanism to sustain cooperation in some hostile network environments where unconditional cooperation is unable to evolve. The cognitive foundations of the mechanism and its implications are discussed.

Max Hartshorn, Artem Kaznatcheev and Thomas Shultz
Journal of Artificial Societies and Social Simulation 16 (3) 7

Kyeywords: Ethnocentrism, Evolution of Cooperation, Evolutionary Game Theory, Minimal Cognition, Prisoner's Dilemma
Abstract: Recent agent-based computer simulations suggest that ethnocentrism, often thought to rely on complex social cognition and learning, may have arisen through biological evolution. From a random start, ethnocentric strategies dominate other possible strategies (selfish, traitorous, and humanitarian) based on cooperation or non-cooperation with in-group and out-group agents. Here we show that ethnocentrism eventually overcomes its closest competitor, humanitarianism, by exploiting humanitarian cooperation across group boundaries as world population saturates. Selfish and traitorous strategies are self-limiting because such agents do not cooperate with agents sharing the same genes. Traitorous strategies fare even worse than selfish ones because traitors are exploited by ethnocentrics across group boundaries in the same manner as humanitarians are, via unreciprocated cooperation. By tracking evolution across time, we find individual differences between evolving worlds in terms of early humanitarian competition with ethnocentrism, including early stages of humanitarian dominance. Our evidence indicates that such variation, in terms of differences between humanitarian and ethnocentric agents, is normally distributed and due to early, rather than later, stochastic differences in immigrant strategies.

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.

Victor Ionut Stoica and Andreas Flache
Journal of Artificial Societies and Social Simulation 17 (1) 5

Kyeywords: Schelling Model, Ethnic Segregation, School Segregation, Model Alignment
Abstract: We address theoretically whether and under what conditions Schelling’s celebrated result of ‘self-organized’ unintended residential segregation may also apply to school segregation. We propose here a computational model of school segregation that is aligned with a corresponding Schelling-type model of residential segregation. To adapt the model for application to school segregation, we move beyond previous work by combining two preference arguments in modeling parents’ school choice, preferences for the ethnic composition of a school and preferences for minimizing the travelling distance to the school. In a set of computational experiments we assessed the effects of population composition and distance preferences in the school model. We found that a preference for nearby schools can suppress the trend towards self-organized segregation obtained in a baseline condition where parents were indifferent towards distance. We then investigated the joint effects of the variation of agents’ “tolerance” for out-group members and distance preference. We found that integrated distributions were preserved under a much broader range of conditions than in the absence of a preference for nearby schools. We conclude that parents’ preferences for nearby schools may be an important factor in tempering for school choice the segregation dynamics known from models of residential segregation.

Mike Farjam, Marco Faillo, Ida Sprinkhuizen-Kuyper and Pim Haselager
Journal of Artificial Societies and Social Simulation 18 (1) 5

Kyeywords: Public Goods Games, Punishment, Cooperation, Reciprocity, Evolution of Cooperation
Abstract: In social dilemmas punishment costs resources, not just from the one who is punished but often also from the punisher and society. Reciprocity on the other side is known to lead to cooperation without the costs of punishment. The questions at hand are whether punishment brings advantages besides its costs, and how its negative side-effects can be reduced to a minimum in an environment populated by agents adopting a form of reciprocity. Various punishment mechanisms have been studied in the economic literature such as unrestricted punishment, legitimate punishment, cooperative punishment, and the hired gun mechanism. In this study all these mechanisms are implemented in a simulation where agents can share resources and may decide to punish other agents when the other agents do not share. Through evolutionary learning agents adapt their sharing/punishing policy. When the availability of resources was restricted, punishment mechanisms in general performed better than no-punishment, although unrestricted punishment was performing worse. When resource availability was high, performance was better in no-punishment conditions with indirect reciprocity. Unrestricted punishment was always the worst performing mechanism. Summarized, this paper shows that, in certain environments, some punishment mechanisms can improve the efficiency of cooperation even if the cooperating system is already based on indirect reciprocity.

Ammar Malik, Andrew Crooks, Hilton Root and Melanie Swartz
Journal of Artificial Societies and Social Simulation 18 (2) 12

Kyeywords: Developing Countries, Urban, Segregation, Land Use, Transport, Agent-Based Modeling
Abstract: Scholars and urban planners have suggested that the key characteristic of leading world cities is that they attract the highest quality human talent through educational and professional opportunities. They offer enabling environments for productive human interactions and the growth of knowledge-based industries which drives economic growth through innovation. Both through hard and soft infrastructure, they offer physical connectivity which fosters human creativity and results in higher income levels. When combined with population density, socio-economic diversity and societal tolerance; the elevated interaction intensity diffuses creativity and improves productivity. In many developing country cities however, rapid urbanization is increasing sprawl and causing deteriorating in public services. We operationalize these insights by creating a stylized agent-based model where heterogeneous and independent decision-making agents interact under the following three scenarios: (1) improved urban transportation investments; (2) mixed land-use regulations; and (3) reduced residential segregation. We find that any combination of these scenarios results in greater population density and enables the diffusion of creativity, thus resulting in economic growth. However, the results demonstrate a clear trade-off between rapid economic progress and socioeconomic equity mainly due to the crowding out of low- and middle-income households from clusters of creativity.

Shade T. Shutters and David Hales
Journal of Artificial Societies and Social Simulation 18 (3) 2

Kyeywords: Tags, Thresholds, Altruism, Evolution, Cooperation, Social Harmonics
Abstract: Several parameters combine to govern the nature of agent interactions in evolutionary social simulations. Previous work has suggested that these parameters may have complex interplay that is obscured when they are not analyzed separately. Here we focus specifically on how three population-level parameters, which govern agent interactions, affect levels of altruism in a population. Specifically we vary how frequently agents interact in a generation, how far along a network they may interact, and the size of the population. We show that the frequency with which an agent interacts with its neighbors during a generation has a strong effect on levels of evolved altruism – provided that those pairings are stochastic. When agents interact equally with all of their neighbors, regardless of how often, minimal levels of altruism evolve. We further report a curious harmonic signature in the level of altruism resulting from the interplay of the benefit-cost ratio of an altruistic act and the number of agent interactions per generation. While the level of altruism is generally an increasing function of the number of pairings per generation, at each instance where pairings equals a multiple of the benefit-cost ratio a sharp discontinuity occurs, precipitating a drop onto a lower-value function. We explore the nature of these discontinuities by examining the temporal dynamics and spatial configuration of agents. Finally, we show that rules for the evolution of cooperation that are based on network density may be inadvertently missing effects that are due to the frequency of interactions and whether those interactions are symmetrical among neighbors.

Erez Hatna and Itzhak Benenson
Journal of Artificial Societies and Social Simulation 18 (4) 15

Kyeywords: Schelling Model, Ethnic Segregation, Residential Dynamics, Heterogeneous Agents
Abstract: The Schelling model is a simple agent-based model that demonstrates how individuals’ relocation decisions can generate residential segregation in cities. Agents belong to one of two groups and occupy cells of rectangular space. Agents react to the fraction of agents of their own group within the neighborhood around their cell. Agents stay put when this fraction is above a given tolerance threshold but seek a new location if the fraction is below the threshold. The model is well-known for its tipping point behavior: an initially random (integrated) pattern remains integrated when the tolerance threshold is below 1/3 but becomes segregated when the tolerance threshold is above 1/3. In this paper, we demonstrate that the variety of the Schelling model’s steady patterns is richer than the segregation–integration dichotomy and contains patterns that consist of segregated patches of each of the two groups, alongside areas where both groups are spatially integrated. We obtain such patterns by considering a general version of the model in which the mechanisms of the agents' interactions remain the same, but the tolerance threshold varies between the agents of both groups. We show that the model produces patterns of mixed integration and segregation when the tolerance threshold of an essential fraction of agents is either low, below 1/5, or high, above 2/3. The emerging mixed patterns are relatively insensitive to the model’s other parameters.

Genki Ichinose, Masaya Saito, Hiroki Sayama and Hugues Bersini
Journal of Artificial Societies and Social Simulation 18 (4) 3

Kyeywords: Evolution of Cooperation, Tag, Spatial Structure, Migration, Segregation
Abstract: Cooperation is ubiquitous in biological and social systems. Previous studies revealed that a preference toward similar appearance promotes cooperation, a phenomenon called tag-mediated cooperation or communitarian cooperation. This effect is enhanced when a spatial structure is incorporated, because space allows agents sharing an identical tag to regroup to form locally cooperative clusters. In spatially distributed settings, one can also consider migration of organisms, which has a potential to further promote evolution of cooperation by facilitating spatial clustering. However, it has not yet been considered in spatial tag-mediated cooperation models. Here we show, using computer simulations of a spatial model of evolutionary games with organismal migration, that tag-based segregation and homophilic cooperation arise for a wide range of parameters. In the meantime, our results also show another evolutionarily stable outcome, where a high level of heterophilic cooperation is maintained in spatially well-mixed patterns. We found that these two different forms of tag-mediated cooperation appear alternately as the parameter for temptation to defect is increased.

Klaus G. Troitzsch
Journal of Artificial Societies and Social Simulation 20 (1) 10

Kyeywords: Theory Reconstruction, Non-Statement View, Schelling Model, Segregation, Axiom
Abstract: The paper uses Schelling’s famous segregation model and a number of extensions to show how a reconstruction of the theory behind these models along the lines of the ‘non-statement view’ on empirical science can contribute to a better understanding of these models and a more straightforward implementation. A short introduction to the procedure of reconstructing a theory is given, using an extremely simple theory from mechanics. The same procedure is then applied to Schelling’s segregation theory. A number of extensions to Schelling’s model are analysed that relax the original idealisations, such as adding dierent tolerance levels between the two subpopulations, assuming inhomogeneous subpopulations and heterogeneous experiences of neighbourhoods, among others. Finally, it is argued that a ‘non-statement view’ reconstruction of a mental model or a verbally expressed theory are relevant for a useful specification for a simulation model.

Thomas Feliciani, Andreas Flache and Jochem Tolsma
Journal of Artificial Societies and Social Simulation 20 (2) 6

Kyeywords: Opinion Dynamics, Polarization, Social Influence, Segregation
Abstract: Increasing ethnic diversity fosters scholarly interest in how the spatial segregation of groups affects opinion polarization in a society. Despite much empirical and theoretical research, there is little consensus in the literature on the causal link between the spatial segregation of two groups and the emergence of opinion polarization. We contribute to the debate by investigating theoretically the conditions under which the former fosters or hinders the latter. We focus on two processes of opinion polarization (negative influence and persuasive argument communication) that, according to previous modeling work, can be expected to make conflicting predictions about the relationship between segregation and opinion polarization. With a Schelling-type agent-based model of residential segregation, we generate initial environments with different levels of group segregation. Then we simulate the two processes of opinion dynamics. We show that the negative influence model predicts segregation to hinder the emergence of opinion polarization. On the other hand, the persuasive argument model predicts that segregation does not substantially foster polarization. Moreover, we explore how the spatial patterns of opinion distribution differ between the models: in particular, we investigate the likelihood that group membership and opinion align. We show that the alignment of group membership and opinions differs between the two opinion formation models, and that the scale at which we measure alignment plays a crucial role.

Gérard Weisbuch
Journal of Artificial Societies and Social Simulation 21 (1) 11

Kyeywords: Inequality, Dynamical Regimes, Lattice, Transitions, Tags
Abstract: We discuss a model of inequity based on iteration of the Nash multi-agent bargaining game on a lattice. Agent's choices are based on a logit function and gradual decay of memories of past profits. Numerical simulations demonstrate the stability of various dynamical regimes, such as disorder, fairness or inequity, according to parameters and initial conditions. When playing the game on a lattice i.e. using neighbouring agent interactions instead of random interaction among the whole agent population, one observes spatial domains and specific patterns in addition to the temporal convergence toward attractors observed when interactions involve any pair of agents. A result specific to the network topology is the co-existence of domains with different regimes, allowing the emergence of the inequity condition even in the absence of tags.

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.

Miranda Simon
Journal of Artificial Societies and Social Simulation 22 (2) 2

Kyeywords: International Migration, Immigration Policy, Return Migration
Abstract: Social network theory (SNT) holds that, once a critical number of migrants have settled in a destination, migration adopts a self-perpetuating character whereby movement tends to follow the `beaten track.' At this point, the migratory flow between two countries will no longer be strongly correlated to macro-level variables such as immigration policy. This implies that migrants from a given origin will continue to concentrate in the same destination even if other destinations offer easier possibilities for entry. The concentration of immigrants from one origin, predicted by SNT, is widely documented. However, we also see evidence of migrant flows reorienting away from locations where co-ethnics have historically settled. I develop an abstract, theory-driven agent-based model to help reconcile the existence of two apparently mutually exclusive outcomes under the framework of SNT. This model, which considers network-driven labor migration from Mexico to the USA from 1990 to 2013, demonstrates that network theory can explain the emergence of both path dependent migration systems as well as systems that shift in reaction to immigration policy, when return migration is taken into account. Return, a severely understudied aspect of migration, can help migration flows adapt to changes in immigration policy and follow the path of least resistance towards a new destination.

Li An, Judy Mak, Shuang Yang, Rebecca Lewison, Douglas A. Stow, Hsiang Ling Chen, Weihua Xu, Lei Shi and Yu Hsin Tsai
Journal of Artificial Societies and Social Simulation 23 (1) 5

Kyeywords: Agent-Based Modeling, Payments for Ecosystem Services, Complex Human-Environment Systems, Guizhou Snub-Nosed Monkey, Migration, Land Use
Abstract: The theory and practice associated with payments for ecosystem services (PES) feature a variety of piecemeal studies related to impacts of socioeconomic, demographic, and environmental variables, lacking efforts in understanding their mutual relationships in a spatially and temporally explicit manner. In addition, PES literature is short of ecological metrics that document the consequences of PES other than land use and land cover and its change. Building on detailed survey data from Fanjingshan National Nature Reserve (FNNR), China, we developed and tested an agent-based model to study the complex interactions among human livelihoods (migration and resource extraction in particular), PES, and the Guizhou golden monkey habitat occupancy over 20 years. We then performed simulation-based experiments testing social and ecological impacts of PES payments as well as human population pressures. The results show that with a steady increase in outmigration, the number of land parcels enrolled in one of China’s major PES programs tends to increase, reach a peak, and then slowly decline, showing a convex trend that converges to a stable number of enrolled parcels regardless of payment levels. Simulated monkey occupancy responds to changes in PES payment levels substantially in edge areas of FNNR. Our model is not only useful for FNNR, but also applicable as a platform to study and further understand human and ecological roles of PES in many other complex human-environment systems, shedding light into key elements, interactions, or relationships in the systems that PES researchers and practitioners should bear in mind. Our research contributes to establishing a scientific basis of PES science that incorporates features in complex systems, offering more realistic, spatially and temporally explicit insights related to PES policy or related interventions.

Ali Termos, Stefano Picascia and Neil Yorke-Smith
Journal of Artificial Societies and Social Simulation 24 (1) 2

Kyeywords: Rent-Gap Theory, Migration, Agent-Based Modelling, Urban Dynamics, Housing, Lebanon
Abstract: Rapid international migration of significant populations generates profound implications for countries in West Asia, Europe, and other regions. The motivation of this work is to develop an agent-based model (ABM) to capture the existence of such migrant and refugee flows, and to explore the effects of these flows on urban dynamics. Advances in agent-based modelling have led to theoretically-grounded spatial agent models of urban dynamics, capturing the dynamics of population, property prices, and regeneration. In this article we leverage such an extant agent-based model founded on the rent-gap theory, as a lens to study the effect of sizeable refugee migration upon a capital city in West Asia. In order to calibrate and validate the simulation model we construct indices for housing prices and other factors. Results from the model, implemented in NetLogo, show the impact of migration shock on the housing market, and identify the relative efficacy of housing intervention policies. Our work progresses towards a tool for policy makers asking what-if questions about the urban environment in the context of migration.

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.

Woi Sok Oh, Álvaro Carmona-Cabrero, Rafael Muñoz-Carpena and Rachata Muneepeerakul
Journal of Artificial Societies and Social Simulation 25 (2) 7

Kyeywords: Agent-Based Model, Human Migration, Factor Configuration, Decision-Making Process, Social Ties
Abstract: Many researchers have addressed what factors should be included in their models of coupled natural-human systems (CNHSs). However, few studies have explored how these factors should be incorporated (factor configuration). Theoretical underpinning of the factor configuration may lead to a better understanding of systematic patterns and sustainable CNHS management. In particular, we ask: (1) can factor configuration explain CNHS behaviors based on its theoretical implications? and (2) when disturbed by shocks, do CNHSs respond differently under varying factor configurations? A proof-of-concept migration agent-based model (ABM) was developed and used as a platform to investigate the effects of factor configuration on system dynamics and outcomes. Here, two factors, social ties and water availability, were assumed to have alternative substitutable, complementary, or adaptable relationships in influencing migration decisions. We analyzed how populations are distributed over different regions along a water availability gradient and how regions are culturally mixed under different factor configurations. We also subjected the system to a shock scenario of dropping 50% of water availability in one region. We found that substitutability acted as a bu er against the effect of water deficiency and prevented cultural mixing of the population by keeping residents in their home regions and slowing down residential responses against the shock. Complementarity led to the sensitive migration behavior of residents, accelerating regional migration and cultural mixing. Adaptability caused residents to stay longer in new regions, which gradually led to a well-mixed cultural condition. All together, substitutability, complementarity, and adaptability gave rise to different emergent patterns. Our findings highlight the importance of how, not just what, factors are included in a CNHS ABM, a lesson that is particularly applicable to models of interdisciplinary problems where factors of diverse nature must be incorporated.

Marcos Pinheiro
Journal of Artificial Societies and Social Simulation 25 (3) 5

Kyeywords: Hunter-Gatherers, Food Sharing, Evolution of Cooperation, Egalitarianism, Agent-Based Model
Abstract: Among social anthropologists, there is virtual consensus that the food-sharing practices of small-scale non-agricultural groups cannot be understood in isolation from the broader repertoire of leveling strategies that prevent would-be dominants from exercising power and influence over likely subordinates. In spite of that widespread view, quantitatively rigorous empirical studies of food sharing and cooperation in small-scale human groups have typically ignored the internal connection between leveling of income and political power, drawing inspiration instead from evolutionary models that are neutral about social role asymmetries. In this paper, I introduce a spatially explicit agent-based model of hunter-gatherer food sharing in which individuals are driven by the goal of maximizing their own income while minimizing income asymmetries among others. Model simulation results show that seven basic patterns of inter-household food transfers described in detail for the Hadza hunters of Tanzania can be simultaneously reproduced with striking accuracy under the assumption that agents selectively support and carry on sharing interactions in ways that maximize their income leveling potential.

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.