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Revisiting Individual Evolutionary Learning in the Cobweb Model – An Illustration of the Virtual Spite-Effect

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  • Jasmina Arifovic
  • Michael Maschek

Abstract

We examine the Cournot oligopoly model in the context of social and individual learning. In both models of learning, firms update their decisions about how much to produce via variants of the genetic algorithm updating procedure. Arifovic (1994) found that both models of social and individual learning converged to the Walrasian, competitive equilibrium. Vriend (2000) reports that the model of social learning converges to the Walrasian equilibrium outcome, while the model of individual learning converges to the Cournot–Nash equilibrium. We revisit the issue and conduct simulations varying elements of the updating algorithms, as well as of the underlying economic model. In the analysis of the outcomes of our simulations, we conclude that the convergence to the Cournot–Nash equilibrium is due to two things: the specific way in which production rules’ performance is evaluated coupled with a specific cost function specification. Copyright Springer 2006

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  • 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.
  • Handle: RePEc:kap:compec:v:28:y:2006:i:4:p:333-354
    DOI: 10.1007/s10614-006-9053-3
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    References listed on IDEAS

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    1. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
    2. Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January.
    3. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
    4. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    5. Vriend, Nicolaas J., 2000. "An illustration of the essential difference between individual and social learning, and its consequences for computational analyses," Journal of Economic Dynamics and Control, Elsevier, vol. 24(1), pages 1-19, January.
    6. Floortje Alkemade & Han Poutré & Hans Amman, 2006. "Robust Evolutionary Algorithm Design for Socio-economic Simulation," Computational Economics, Springer;Society for Computational Economics, vol. 28(4), pages 355-370, November.
    7. Jasmina Arifovic & John Ledyard, 2004. "Scaling Up Learning Models in Public Good Games," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 6(2), pages 203-238, May.
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    Cited by:

    1. Michael Maschek, 2016. "Economic Modeling Using Evolutionary Algorithms: The Influence of Mutation on the Premature Convergence Effect," Computational Economics, Springer;Society for Computational Economics, vol. 47(2), pages 297-319, February.
    2. Uehara, Takuro, 2013. "Ecological threshold and ecological economic threshold: Implications from an ecological economic model with adaptation," Ecological Economics, Elsevier, vol. 93(C), pages 374-384.
    3. Arifovic, Jasmina & Karaivanov, Alexander, 2010. "Learning by doing vs. learning from others in a principal-agent model," Journal of Economic Dynamics and Control, Elsevier, vol. 34(10), pages 1967-1992, October.
    4. Thomas Vallée & Murat Yıldızoğlu, 2013. "Can They Beat the Cournot Equilibrium? Learning with Memory and Convergence to Equilibria in a Cournot Oligopoly," Computational Economics, Springer;Society for Computational Economics, vol. 41(4), pages 493-516, April.
    5. Vallée, Thomas & YIldIzoglu, Murat, 2009. "Convergence in the finite Cournot oligopoly with social and individual learning," Journal of Economic Behavior & Organization, Elsevier, vol. 72(2), pages 670-690, November.
    6. Liu, Jia & Riyanto, Yohanes E. & Zhang, Ruike, 2020. "Firing the right bullets: Exploring the effectiveness of the hired-gun mechanism in the provision of public goods," Journal of Economic Behavior & Organization, Elsevier, vol. 170(C), pages 222-243.
    7. Michael K. Maschek, 2015. "Particle Swarm Optimization in Agent‐Based Economic Simulations of the Cournot Market Model," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 22(2), pages 133-152, April.
    8. Anufriev, Mikhail & Kopányi, Dávid, 2018. "Oligopoly game: Price makers meet price takers," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 84-103.
    9. Liu, Jia & Riyanto, Yohanes Eko & Zhang, Ruike, 2017. "How Large Should the “Bullets” be? Dissecting the Role of Unilateral and Tie Punishment in the Provision of Public Goods," MPRA Paper 80388, University Library of Munich, Germany.
    10. Alós-Ferrer, Carlos & Buckenmaier, Johannes, 2017. "Cournot vs. Walras: A reappraisal through simulations," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 257-272.
    11. 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.
    12. Herbert Dawid & Philipp Harting, 2012. "Capturing Firm Behavior in Agent-based Models of Industry Evolution and Macroeconomic Dynamics," Chapters, in: Guido Buenstorf (ed.), Evolution, Organization and Economic Behavior, chapter 6, Edward Elgar Publishing.
    13. Floortje Alkemade & Han Poutré & Hans Amman, 2006. "Robust Evolutionary Algorithm Design for Socio-economic Simulation," Computational Economics, Springer;Society for Computational Economics, vol. 28(4), pages 355-370, November.
    14. Tong Zhang & B. Brorsen, 2009. "Particle Swarm Optimization Algorithm for Agent-Based Artificial Markets," Computational Economics, Springer;Society for Computational Economics, vol. 34(4), pages 399-417, November.
    15. Ilkka Leppänen, 2018. "Evolutionarily stable conjectures and other regarding preferences in duopoly games," Journal of Evolutionary Economics, Springer, vol. 28(2), pages 347-364, April.

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    More about this item

    Keywords

    social learning; individual learning; spite effect; robustness; B41; C63; C81; D83; H41;
    All these keywords.

    JEL classification:

    • B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • H41 - Public Economics - - Publicly Provided Goods - - - Public Goods

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