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Learning to alternate

Author

Listed:
  • Jasmina Arifovic

    (Simon Fraser University)

  • John Ledyard

    (California Institute of Technology)

Abstract

The Individual Evolutionary Learning (IEL) model explains human subjects’ behavior in a wide range of repeated games which have unique Nash equilibria. Using a variation of ‘better response’ strategies, IEL agents quickly learn to play Nash equilibrium strategies and their dynamic behavior is like that of humans subjects. In this paper we study whether IEL can also explain behavior in games with gains from coordination. We focus on the simplest such game: the 2 person repeated Battle of Sexes game. In laboratory experiments, two patterns of behavior often emerge: players either converge rapidly to one of the stage game Nash equilibria and stay there or learn to coordinate their actions and alternate between the two Nash equilibria every other round. We show that IEL explains this behavior if the human subjects are truly in the dark and do not know or believe they know their opponent’s payoffs. To explain the behavior when agents are not in the dark, we need to modify the basic IEL model and allow some agents to begin with a good idea about how to play. We show that if the proportion of inspired agents with good ideas is chosen judiciously, the behavior of IEL agents looks remarkably similar to that of human subjects in laboratory experiments.

Suggested Citation

  • Jasmina Arifovic & John Ledyard, 2018. "Learning to alternate," Experimental Economics, Springer;Economic Science Association, vol. 21(3), pages 692-721, September.
    • Handle: RePEc:kap:expeco:v:21:y:2018:i:3:d:10.1007_s10683-018-9568-1
    DOI: 10.1007/s10683-018-9568-1
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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. John Huyck & Raymond Battalio & Frederick Rankin, 2007. "Selection dynamics and adaptive behavior without much information," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 33(1), pages 53-65, October.
    3. Van Huyck, John B & Battalio, Raymond C & Beil, Richard O, 1990. "Tacit Coordination Games, Strategic Uncertainty, and Coordination Failure," American Economic Review, American Economic Association, vol. 80(1), pages 234-248, March.
    4. Timothy Cason & Sau-Him Lau & Vai-Lam Mui, 2013. "Learning, teaching, and turn taking in the repeated assignment game," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 54(2), pages 335-357, October.
    5. Arifovic, Jasmina & Ledyard, John, 2007. "Call market book information and efficiency," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1971-2000, June.
    6. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
    7. Bednar, Jenna & Chen, Yan & Liu, Tracy Xiao & Page, Scott, 2012. "Behavioral spillovers and cognitive load in multiple games: An experimental study," Games and Economic Behavior, Elsevier, vol. 74(1), pages 12-31.
    8. Arifovic, Jasmina & Ledyard, John, 2011. "A behavioral model for mechanism design: Individual evolutionary learning," Journal of Economic Behavior & Organization, Elsevier, vol. 78(3), pages 374-395, May.
    9. Van Huyck, John B & Cook, Joseph P & Battalio, Raymond C, 1994. "Selection Dynamics, Asymptotic Stability, and Adaptive Behavior," Journal of Political Economy, University of Chicago Press, vol. 102(5), pages 975-1005, October.
    10. Jasmina Arifovic & John Ledyard, 2012. "Individual Evolutionary Learning, Other-regarding Preferences, and the Voluntary Contributions Mechanism," Discussion Papers wp12-01, Department of Economics, Simon Fraser University.
    11. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    12. Ido Erev & Eyal Ert & Alvin E. Roth, 2010. "A Choice Prediction Competition for Market Entry Games: An Introduction," Games, MDPI, vol. 1(2), pages 1-20, May.
    13. John Huyck & Raymond Battalio & Frederick Rankin, 2007. "Evidence on learning in coordination games," Experimental Economics, Springer;Economic Science Association, vol. 10(3), pages 205-220, September.
    14. Sonsino, Doron & Sirota, Julia, 2003. "Strategic pattern recognition--experimental evidence," Games and Economic Behavior, Elsevier, vol. 44(2), pages 390-411, August.
    15. Van Huyck, John B. & Cook, Joseph P. & Battalio, Raymond C., 1997. "Adaptive behavior and coordination failure," Journal of Economic Behavior & Organization, Elsevier, vol. 32(4), pages 483-503, April.
    16. Cheung, Yin-Wong & Friedman, Daniel, 1997. "Individual Learning in Normal Form Games: Some Laboratory Results," Games and Economic Behavior, Elsevier, vol. 19(1), pages 46-76, April.
    17. Ioannou, Christos A. & Romero, Julian, 2014. "A generalized approach to belief learning in repeated games," Games and Economic Behavior, Elsevier, vol. 87(C), pages 178-203.
    18. 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.
    19. John B. Van Huyck & Raymond C. Battalio & Richard O. Beil, 1991. "Strategic Uncertainty, Equilibrium Selection, and Coordination Failure in Average Opinion Games," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(3), pages 885-910.
    20. Arifovic, Jasmina & Ledyard, John, 2012. "Individual evolutionary learning, other-regarding preferences, and the voluntary contributions mechanism," Journal of Public Economics, Elsevier, vol. 96(9-10), pages 808-823.
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    Cited by:

    1. Zhao, Shuchen, 2021. "Taking turns in continuous time," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 257-279.
    2. Sheryl Ball & Chetan Dave & Stefan Dodds, 2023. "Enumerating rights: more is not always better," Public Choice, Springer, vol. 196(3), pages 403-425, September.
    3. Cars Hommes & Stefanie J. Huber & Daria Minina & Isabelle Salle, 2023. "Learning in a Complex World: Insights from an OLG Lab Experiment," Staff Working Papers 23-13, Bank of Canada.
    4. Chernov, G. & Susin, I., 2019. "Models of learning in games: An overview," Journal of the New Economic Association, New Economic Association, vol. 44(4), pages 77-125.
    5. Chernomaz, K. & Goertz, J.M.M., 2023. "(A)symmetric equilibria and adaptive learning dynamics in small-committee voting," Journal of Economic Dynamics and Control, Elsevier, vol. 147(C).
    6. Konstantin Chatziathanasiou & Svenja Hippel & Michael Kurschilgen, 2020. "Property, Redistribution, and the Status Quo," Munich Papers in Political Economy 02, Munich School of Politics and Public Policy and the School of Management at the Technical University of Munich.
    7. He, Simin & Wu, Jiabin, 2020. "Compromise and coordination: An experimental study," Games and Economic Behavior, Elsevier, vol. 119(C), pages 216-233.
    8. Arifovic, Jasmina & Duffy, John & Jiang, Janet Hua, 2023. "Adoption of a new payment method: Experimental evidence," European Economic Review, Elsevier, vol. 154(C).
    9. Konstantin Chatziathanasiou & Svenja Hippel & Michael Kurschilgen, 2021. "Property, redistribution, and the status quo: a laboratory study," Experimental Economics, Springer;Economic Science Association, vol. 24(3), pages 919-951, September.
    10. Anufriev, Mikhail & Arifovic, Jasmina & Ledyard, John & Panchenko, Valentyn, 2022. "The role of information in a continuous double auction: An experiment and learning model," Journal of Economic Dynamics and Control, Elsevier, vol. 141(C).

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    More about this item

    Keywords

    Battle of Sexes; Alternation; Learning;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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