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

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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," Documents de travail du Centre d'Economie de la Sorbonne bla07017, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  • Handle: RePEc:mse:cesdoc:bla07017
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    Citations

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    Cited by:

    1. Burkhard Schipper, 2015. "Strategic teaching and learning in games," Working Papers 151, University of California, Davis, Department of Economics.
    2. 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.
    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. repec:kap:theord:v:82:y:2017:i:4:d:10.1007_s11238-016-9579-3 is not listed on IDEAS
    8. Jordi Brandts & David J. Cooper, 2015. "Centralized vs. Decentralized Management: an Experimental Study," Working Papers 854, Barcelona Graduate 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. 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.
    11. Mengel, Friederike, 2014. "Learning by (limited) forward looking players," Journal of Economic Behavior & Organization, Elsevier, vol. 108(C), pages 59-77.

    More about this item

    Keywords

    Game theory; teaching; beliefs; experiment;

    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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