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Agent_Zero:Toward Neurocognitive Foundations for Generative Social Science

Author

Listed:
  • Joshua M. Epstein

    (The Johns Hopkins University)

Abstract

The Final Volume of the Groundbreaking Trilogy on Agent-Based Modeling In this pioneering synthesis, Joshua Epstein introduces a new theoretical entity: Agent_Zero. This software individual, or "agent," is endowed with distinct emotional/affective, cognitive/deliberative, and social modules. Grounded in contemporary neuroscience, these internal components interact to generate observed, often far-from-rational, individual behavior. When multiple agents of this new type move and interact spatially, they collectively generate an astonishing range of dynamics spanning the fields of social conflict, psychology, public health, law, network science, and economics. Epstein weaves a computational tapestry with threads from Plato, Hume, Darwin, Pavlov, Smith, Tolstoy, Marx, James, and Dostoevsky, among others. This transformative synthesis of social philosophy, cognitive neuroscience, and agent-based modeling will fascinate scholars and students of every stripe. Epstein’s computer programs are provided in the book or on its Princeton University Press website, along with movies of his "computational parables." Agent_Zero is a signal departure in what it includes (e.g., a new synthesis of neurally grounded internal modules), what it eschews (e.g., standard behavioral imitation), the phenomena it generates (from genocide to financial panic), and the modeling arsenal it offers the scientific community. For generative social science, Agent_Zero presents a groundbreaking vision and the tools to realize it.

Suggested Citation

  • Joshua M. Epstein, 2014. "Agent_Zero:Toward Neurocognitive Foundations for Generative Social Science," Economics Books, Princeton University Press, edition 1, number 10169.
    • Handle: RePEc:pup:pbooks:10169
    as

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    Citations

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    Cited by:

    1. Mitja Steinbacher & Matthias Raddant & Fariba Karimi & Eva Camacho Cuena & Simone Alfarano & Giulia Iori & Thomas Lux, 2021. "Advances in the agent-based modeling of economic and social behavior," SN Business & Economics, Springer, vol. 1(7), pages 1-24, July.
    2. Christopher J Lynch & Saikou Y Diallo & Hamdi Kavak & Jose J Padilla, 2020. "A content analysis-based approach to explore simulation verification and identify its current challenges," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-33, May.
    3. Galesic, Mirta & Stein, D.L., 2019. "Statistical physics models of belief dynamics: Theory and empirical tests," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 275-294.
    4. Sebastian Daza & L. Kurt Kreuger, 2021. "Agent-Based Models for Assessing Complex Statistical Models: An Example Evaluating Selection and Social Influence Estimates from SIENA," Sociological Methods & Research, , vol. 50(4), pages 1725-1762, November.
    5. Mark G. Orr & Christian Lebiere & Andrea Stocco & Peter Pirolli & Bianica Pires & William G. Kennedy, 2019. "Multi-scale resolution of neural, cognitive and social systems," Computational and Mathematical Organization Theory, Springer, vol. 25(1), pages 4-23, March.
    6. Adrien Querbes, 2018. "Banned from the sharing economy: an agent-based model of a peer-to-peer marketplace for consumer goods and services," Journal of Evolutionary Economics, Springer, vol. 28(3), pages 633-665, August.

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