Agent-based Modeling: A Guide for Social Psychologists

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Agent-based Modeling: A Guide for Social Psychologists

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Title: Agent-based Modeling: A Guide for Social Psychologists
Author: Jackson, Joshua Conrad; Rand, David; Lewis, Kevin; Norton, Michael Irwin; Gray, Kurt

Note: Order does not necessarily reflect citation order of authors.

Citation: Jackson, Joshua Conrad, David Rand, Kevin Lewis, Michael I. Norton, and Kurt Gray. "Agent-based Modeling: A Guide for Social Psychologists." Social Psychological & Personality Science (in press).
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Abstract: Agent-based modeling is a longstanding but underused method that allows researchers to simulate artificial worlds for hypothesis testing and theory building. Agent-based models (ABMs) offer unprecedented control and statistical power by allowing researchers to precisely specify the behavior of any number of agents and observe their interactions over time. ABMs are especially useful when investigating group behavior or evolutionary processes and can uniquely reveal non-linear dynamics and emergence—the process whereby local interactions aggregate into often surprising collective phenomena, such as spatial segregation and relational homophily. We review several illustrative ABMs, describe the strengths and limitations of this method, and address two misconceptions about ABMs: reductionism and “you get out what you put in.” We also offer maxims for good and bad ABMs, give practical tips for beginner modelers, and include a list of resources and other models. We conclude with a 7-step guide to creating your own model.
Published Version: http://journals.sagepub.com/loi/spp
Terms of Use: This article is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#OAP
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:30194529
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