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Agent-Based Computational Economics: A Brief Guide to the Literature

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  • Leigh Tesfatsion

    (Iowa State University)

Abstract

Agent-based computational economics (ACE)is the computational study of economies modelled as evolving systems of autonomous interacting agents. This short paper is a brief guide to recent ACE research. For more information, visit the ACE Web site at http://www.econ.iastate.edu/tesfatsi/ace.htm. Resources available at the ACE Web site include surveys, an annotated syllabus of readings, software, teaching materials, pointers to research on economic and social network formation, and pointers to individual researchers and research groups.

Suggested Citation

  • Leigh Tesfatsion, 2000. "Agent-Based Computational Economics: A Brief Guide to the Literature," Computational Economics 0004001, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpco:0004001
    Note: Type of Document - pdf; prepared on IBM PC - PC-TEX; to print on HP/PostScript/; pages: 6 ; figures: none
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/comp/papers/0004/0004001.pdf
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    References listed on IDEAS

    as
    1. McFadzean, David & Tesfatsion, Leigh, 1999. "A C++ Platform for the Evolution of Trade Networks," Computational Economics, Springer;Society for Computational Economics, vol. 14(1-2), pages 109-134, October.
    2. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, December.
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    Cited by:

    1. Roberto Leombruni & Matteo Richiardi, 2006. "LABORsim: An Agent-Based Microsimulation of Labour Supply – An Application to Italy," Computational Economics, Springer;Society for Computational Economics, vol. 27(1), pages 63-88, February.
    2. Roberto Leombruni, 2002. "The Methodological Status of Agent-Based Simulations," LABORatorio R. Revelli Working Papers Series 19, LABORatorio R. Revelli, Centre for Employment Studies.
    3. Sasaki, Yuya, 2004. "The Equivalence Of Evolutionary Games And Distributed Monte Carlo Learning," Economics Research Institute, ERI Series 28338, Utah State University, Economics Department.
    4. Denis Phan & Stephane Pajot & Jean-Pierre Nadal, 2003. "The Monopolist's Market with Discrete Choices and Network Externality Revisited: Small-Worlds, Phase Transition and Avalanches in an ACE Framework," Computing in Economics and Finance 2003 150, Society for Computational Economics.
    5. Davide Bazzana, 2020. "Ageing population and pension system sustainability: reforms and redistributive implications," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(3), pages 971-992, October.
    6. Matteo Richiardi & Roberto Leombruni & Nicole J. Saam & Michele Sonnessa, 2006. "A Common Protocol for Agent-Based Social Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(1), pages 1-15.

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    More about this item

    Keywords

    Agent-based computational economics;

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments

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