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

Author

Listed:
  • 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-00145436v1
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    2. Burkhard C. Schipper, 2022. "Strategic Teaching and Learning in Games," American Economic Journal: Microeconomics, American Economic Association, vol. 14(3), pages 321-352, August.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. David J. Cooper & Jordi Brandts, 2015. "Centralized vs. Decentralized Management: an Experimental Study," Working Papers 854, Barcelona School of Economics.
    9. Bryan McCannon, 2011. "Coordination between a sophisticated and fictitious player," Journal of Economics, Springer, vol. 102(3), pages 263-273, April.
    10. 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.
    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. Mengel, Friederike, 2014. "Learning by (limited) forward looking players," Journal of Economic Behavior & Organization, Elsevier, vol. 108(C), pages 59-77.
    13. Burkhard Schipper, 2015. "Strategic teaching and learning in games," Working Papers 151, University of California, Davis, Department of Economics.
    14. Burkhard C. Schipper, 2019. "Dynamic Exploitation of Myopic Best Response," Dynamic Games and Applications, Springer, vol. 9(4), pages 1143-1167, December.
    15. 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.
    16. He, Simin & Wu, Jiabin, 2020. "Compromise and coordination: An experimental study," Games and Economic Behavior, Elsevier, vol. 119(C), pages 216-233.
    17. 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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    Keywords

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    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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