A standard form of citation of this article is:
Heath, Brian, Hill, Raymond and Ciarallo, Frank (2009). 'A Survey of Agent-Based Modeling Practices (January 1998 to July 2008)'. Journal of Artificial Societies and Social Simulation 12(4)9 <https://www.jasss.org/12/4/9.html>.
The following can be copied and pasted into a Bibtex bibliography file, for use with the LaTeX text processor:
@article{heath2009,
title = {A Survey of Agent-Based Modeling Practices (January 1998 to July 2008)},
author = {Heath, Brian and Hill, Raymond and Ciarallo, Frank},
journal = {Journal of Artificial Societies and Social Simulation},
ISSN = {1460-7425},
volume = {12},
number = {4},
pages = {9},
year = {2009},
URL = {https://www.jasss.org/12/4/9.html},
keywords = {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.},
}The following can be copied and pasted into a text file, which can then be imported into a reference database that supports imports using the RIS format, such as Reference Manager and EndNote.
TY - JOUR
TI - A Survey of Agent-Based Modeling Practices (January 1998 to July 2008)
AU - Heath, Brian
AU - Hill, Raymond
AU - Ciarallo, Frank
Y1 - 2009/10/31/
JO - Journal of Artificial Societies and Social Simulation
SN - 1460-7425
VL - 12
IS - 4
SP - 9
UR - https://www.jasss.org/12/4/9.html
KW - Agent-Based Modeling
KW - Survey
KW - Current Practices
KW - Simulation Validation
KW - Simulation Purpose
N2 - 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.
ER -