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Dumbing down rational players: learning and teaching in an experimental game

Author

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  • Antoine Terracol

    (GREMARS - Groupe de Recherches Modélisation Appliquée à la Recherche en Sciences Sociales - Université de Lille, Sciences Humaines et Sociales, CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Jonathan Vaksmann

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

This paper uses experimental data to examine the existence of a teaching strategy among bounded rational players. If players realize that their own actions modify their opponent's beliefs and actions, they might play certain actions to this specific end; and forego immediate payoffs if the expected payoffs if the expected payoff gain from a teaching strategy is high enough. Our results support the existence of a teaching strategy in several ways: First they show that players update their beliefs in order to take account of the reaction of their opponents to their own action. Second, we examine if players actually use a teaching strategy by playing an action that induces a poor immediate payoff but is likely to modify the opponent's behavior so that a preferable outcome might emerge in the future. We find strong evidence of such a strategy in the data and confirm this finding within a logistic model which suggests that the future expected payoff that could arise from a teaching strategy has indeed a significant impact on choice probabilities. Finally, we investigate the effective impact of a teaching strategy on achieved outcomes and find that efficient teachers can successfully use teaching in order to reach their favorite outcome at the expense of their opponents.

Suggested Citation

  • Antoine Terracol & Jonathan Vaksmann, 2007. "Dumbing down rational players: learning and teaching in an experimental game," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00145436, HAL.
  • Handle: RePEc:hal:cesptp:halshs-00145436
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00145436
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    Citations

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    Cited by:

    1. Burkhard C. Schipper, 2022. "Strategic Teaching and Learning in Games," American Economic Journal: Microeconomics, American Economic Association, vol. 14(3), pages 321-352, August.
    2. Kyle Hyndman & Antoine Terracol & Jonathan Vaksmann, 2009. "Learning and sophistication in coordination games," Experimental Economics, Springer;Economic Science Association, vol. 12(4), pages 450-472, December.
    3. Burkhard Schipper, 2015. "Strategic teaching and learning in games," Working Papers 151, University of California, Davis, Department of Economics.
    4. David Danz & Dietmar Fehr & Dorothea Kübler, 2012. "Information and beliefs in a repeated normal-form game," Experimental Economics, Springer;Economic Science Association, vol. 15(4), pages 622-640, December.
    5. Burkhard C. Schipper, 2019. "Dynamic Exploitation of Myopic Best Response," Dynamic Games and Applications, Springer, vol. 9(4), pages 1143-1167, December.
    6. He, Simin & Wu, Jiabin, 2020. "Compromise and coordination: An experimental study," Games and Economic Behavior, Elsevier, vol. 119(C), pages 216-233.
    7. Kyle Hyndman & Antoine Terracol & Jonathan Vaksmann, 2010. "Strategic interactions and belief formation: an experiment," Applied Economics Letters, Taylor & Francis Journals, vol. 17(17), pages 1681-1685.
    8. Kyle Hyndman & Dorothée Honhon, 2020. "Flexibility in Long-Term Relationships: An Experimental Study," Manufacturing & Service Operations Management, INFORMS, vol. 22(2), pages 273-291, March.
    9. Masiliūnas, Aidas, 2017. "Overcoming coordination failure in a critical mass game: Strategic motives and action disclosure," Journal of Economic Behavior & Organization, Elsevier, vol. 139(C), pages 214-251.
    10. 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.
    11. Masiliūnas, Aidas, 2019. "Overcoming inefficient lock-in in coordination games with sophisticated and myopic players," Mathematical Social Sciences, Elsevier, vol. 100(C), pages 1-12.
    12. Flip Klijn & Marc Vorsatz, 2017. "Outsourcing with identical suppliers and shortest-first policy: a laboratory experiment," Theory and Decision, Springer, vol. 82(4), pages 597-615, April.
    13. Jordi Brandts & David J. Cooper, 2015. "Centralized vs. Decentralized Management: an Experimental Study," Working Papers 854, Barcelona School of Economics.
    14. Bryan McCannon, 2011. "Coordination between a sophisticated and fictitious player," Journal of Economics, Springer, vol. 102(3), pages 263-273, April.
    15. Mengel, Friederike, 2014. "Learning by (limited) forward looking players," Journal of Economic Behavior & Organization, Elsevier, vol. 108(C), pages 59-77.
    16. Jordi Brandts & David J. Cooper & Enrique Fatas & Shi Qi, 2016. "Stand by Me—Experiments on Help and Commitment in Coordination Games," Management Science, INFORMS, vol. 62(10), pages 2916-2936, October.

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    More about this item

    Keywords

    Game theory; teaching; beliefs; experiment; Théorie des jeux; croyances; expérimentation;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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