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Agent-Based Computational Models and Generative Social Science

In: Generative Social Science Studies in Agent-Based Computational Modeling

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  • Joshua M. Epstein

    (Brookings Institution, Brookings-Johns Hopkins Center on Social and Economic Dynamics, Santa Fe Institute)

Abstract

Agent-based computational modeling is changing the face of social science. In Generative Social Science , Joshua Epstein argues that this powerful, novel technique permits the social sciences to meet a fundamentally new standard of explanation, in which one "grows" the phenomenon of interest in an artificial society of interacting agents: heterogeneous, boundedly rational actors, represented as mathematical or software objects. After elaborating this notion of generative explanation in a pair of overarching foundational chapters, Epstein illustrates it with examples chosen from such far-flung fields as archaeology, civil conflict, the evolution of norms, epidemiology, retirement economics, spatial games, and organizational adaptation. In elegant chapter preludes, he explains how these widely diverse modeling studies support his sweeping case for generative explanation. This book represents a powerful consolidation of Epstein's interdisciplinary research activities in the decade since the publication of his and Robert Axtell's landmark volume, Growing Artificial Societies . Beautifully illustrated, Generative Social Science includes a CD that contains animated movies of core model runs, and programs allowing users to easily change assumptions and explore models, making it an invaluable text for courses in modeling at all levels.

Suggested Citation

  • Joshua M. Epstein, 2007. "Agent-Based Computational Models and Generative Social Science," Introductory Chapters, in: Generative Social Science Studies in Agent-Based Computational Modeling, Princeton University Press.
  • Handle: RePEc:pup:chapts:8277-1
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    References listed on IDEAS

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    Cited by:

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    2. Andrew Crooks & Andrew Hudson-Smith & Joel Dearden, 2009. "Agent Street: An Environment for Exploring Agent-Based Models in Second Life," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(4), pages 1-10.
    3. D'Orazio, Paola, 2019. "Income inequality, consumer debt, and prudential regulation: An agent-based approach to study the emergence of crises and financial instability," Economic Modelling, Elsevier, vol. 82(C), pages 308-331.
    4. Malik, Ammar A. & Crooks, Andrew T. & Root, Hilton L., 2013. "Can Pakistan have creative cities? An agent based modeling approach with preliminary application to Karachi:," PSSP working papers 13, International Food Policy Research Institute (IFPRI).

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