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On economic applications of the genetic algorithm: a model of the cobweb type

Author

Listed:
  • Michael Kopel

    (Department of Managerial Economics and Industrial Organization, Vienna University of Technology, Wien, Austria)

  • Herbert Dawid

    (Department of Management Science, University of Vienna, Br, nnerstrasse 72, A-1210 Wien, Austria)

Abstract

This paper explores the idea of using artificial adaptive agents in economic theory. In particular, we use Genetic Algorithms (GAs) to model the learning behavior of a population of adaptive and boundedly rational agents interacting in an economic system. We analyze the behavior of a GA in two versions of a model of the cobweb-type, one in which firms make only quantity choices, and the other one in which firms first decide to exit or to stay in the market, and subsequently decide how much to produce. We present simulations with different coding schemes and interpret the rather surprising differences between the results for different setups by employing the mathematical theory for GAs with state-dependent fitness functions. In particular, we explain the relationship between coding and convergence properties of GAs.

Suggested Citation

  • Michael Kopel & Herbert Dawid, 1998. "On economic applications of the genetic algorithm: a model of the cobweb type," Journal of Evolutionary Economics, Springer, vol. 8(3), pages 297-315.
    • Handle: RePEc:spr:joevec:v:8:y:1998:i:3:p:297-315
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    Cited by:

    1. Safarzynska, Karolina & van den Bergh, Jeroen C.J.M., 2011. "Beyond replicator dynamics: Innovation-selection dynamics and optimal diversity," Journal of Economic Behavior & Organization, Elsevier, vol. 78(3), pages 229-245, May.
    2. Mattheos Protopapas & Francesco Battaglia & Elias Kosmatopoulo, 2008. "Coevolutionary Genetic Algorithms for Establishing Nash Equilibrium in Symmetric Cournot Games," Working Papers 004, COMISEF.
    3. Marten Graubner & Richard J. Sexton, 2023. "More competitive than you think? Pricing and location of processing firms in agricultural markets," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(3), pages 784-808, May.
    4. Graupner, Marten, 2011. "The Spatial Agent-based Competition Model (SpAbCoM) [Das räumliche agenten-basierte Wettbewerbsmodell SpAbCoM]," IAMO Discussion Papers 135, Leibniz Institute of Agricultural Development in Transition Economies (IAMO).
    5. Balmann, Alfons & Musshoff, Oliver, 2002. "Is The "Standard Real Options Approach" Appropriate For Investment Decisions In Hog Production?," 2002 Annual meeting, July 28-31, Long Beach, CA 19897, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. repec:zbw:iamodp:109915 is not listed on IDEAS
    7. Balmann, Alfons & Musshoff, Oliver, 2002. "Real Options and Competition: The Impact of Depreciation and Reinvestment," 2002 International Congress, August 28-31, 2002, Zaragoza, Spain 24934, European Association of Agricultural Economists.
    8. Michael Neugart & Jan Tuinstra, 2003. "Endogenous fluctuations in the demand for education," Journal of Evolutionary Economics, Springer, vol. 13(1), pages 29-51, February.
    9. Smith, Peter, 2004. "Reworking the Standard Model of Competitive Markets: The Role of Fuzzy Logic and Genetic Algorithms in Modelling Complex Non-Linear Economic System," General Discussion Papers 30569, University of Manchester, Institute for Development Policy and Management (IDPM).
    10. Serguei Kaniovski, 2005. "Product differentiation and competitive selection," Journal of Evolutionary Economics, Springer, vol. 15(5), pages 567-580, November.
    11. Balmann, Alfons & Kataria, Karin & Musshoff, Oliver, 2013. "Investment reluctance in supply chains: An agent-based real options approach," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 3(2A), pages 1-10.
    12. Mikhail Anufriev & Cars Hommes & Tomasz Makarewicz, 2019. "Simple Forecasting Heuristics that Make us Smart: Evidence from Different Market Experiments," Journal of the European Economic Association, European Economic Association, vol. 17(5), pages 1538-1584.
    13. Arifovic, Jasmina & He, Xue-zhong & Wei, Lijian, 2022. "Machine learning and speed in high-frequency trading," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    14. Graubner, Marten & Sexton, Richard J., 2021. "Spatial competition in agricultural procurement markets," 2021 Annual Meeting, August 1-3, Austin, Texas 313962, Agricultural and Applied Economics Association.
    15. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
    16. Domenico Colucci & Vincenzo Valori, 2011. "Can Endogenous Participation Explain Price Volatility? Evidence from an Agent-Based Cobweb Model," Computational Economics, Springer;Society for Computational Economics, vol. 38(3), pages 425-437, October.
    17. Dawid, Herbert, 1999. "On the convergence of genetic learning in a double auction market," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1545-1567, September.
    18. Sylvie Geisendorf, 2011. "Internal selection and market selection in economic Genetic Algorithms," Journal of Evolutionary Economics, Springer, vol. 21(5), pages 817-841, December.
    19. Ludo Waltman & Nees Eck & Rommert Dekker & Uzay Kaymak, 2011. "Economic modeling using evolutionary algorithms: the effect of a binary encoding of strategies," Journal of Evolutionary Economics, Springer, vol. 21(5), pages 737-756, December.
    20. Thomas Riechmann, 2006. "Cournot or Walras? Long-Run Results in Oligopoly Games," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 162(4), pages 702-720, December.
    21. Jasmina Arifovic & Michael Maschek, 2006. "Revisiting Individual Evolutionary Learning in the Cobweb Model – An Illustration of the Virtual Spite-Effect," Computational Economics, Springer;Society for Computational Economics, vol. 28(4), pages 333-354, November.
    22. Vinícius Ferraz & Thomas Pitz, 2024. "Analyzing the Impact of Strategic Behavior in an Evolutionary Learning Model Using a Genetic Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 437-475, February.
    23. Graubner, Marten, 2011. "The Spatial Agent-based Competition Model (SpAbCoM)," IAMO Discussion Papers 109915, Institute of Agricultural Development in Transition Economies (IAMO).

    More about this item

    Keywords

    Cobweb model ; Genetic algorithms ; Learning ; Artificial economic agents;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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