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The reinforcement heuristic in normal form games

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  • Alós-Ferrer, Carlos
  • Ritschel, Alexander

Abstract

We analyze simple reinforcement-based behavioral rules in 3 × 3 games through choice data and response times. We argue that there is a large overlap between reinforcement-based heuristics (win-stay, lose-shift) and the more “rational” behavioral rule of myopic best reply. However, evidence from response times shows that choices in agreement with the common prescription of those rules are comparatively fast, and choices of the form “lose-shift” occur more frequently for larger differences with bygone payoffs. Both observations speak in favor of reinforcement processes as a cognitive shortcut for apparent myopic best reply, and advise caution when interpreting behavioral results in favor of optimizing behavior.

Suggested Citation

  • Alós-Ferrer, Carlos & Ritschel, Alexander, 2018. "The reinforcement heuristic in normal form games," Journal of Economic Behavior & Organization, Elsevier, vol. 152(C), pages 224-234.
  • Handle: RePEc:eee:jeborg:v:152:y:2018:i:c:p:224-234
    DOI: 10.1016/j.jebo.2018.06.014
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    References listed on IDEAS

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    Cited by:

    1. Francesco Fallucchi & Jan Niederreiter & Massimo Riccaboni, 2021. "Learning and dropout in contests: an experimental approach," Theory and Decision, Springer, vol. 90(2), pages 245-278, March.
    2. repec:cup:judgdm:v:14:y:2019:i:4:p:381-394 is not listed on IDEAS
    3. Arkady Konovalov & Ian Krajbich, 2019. "Revealed strength of preference: Inference from response times," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 14(4), pages 381-394, July.
    4. Carlos Alós-Ferrer & Ernst Fehr & Nick Netzer, 2021. "Time Will Tell: Recovering Preferences When Choices Are Noisy," Journal of Political Economy, University of Chicago Press, vol. 129(6), pages 1828-1877.
    5. Ayşegül Engin, 2021. "The cognitive ability and working memory framework: Interpreting cognitive reflection test results in the domain of the cognitive experiential theory," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(1), pages 227-245, March.
    6. Carlos Alós-Ferrer & Michele Garagnani, 2022. "Strength of preference and decisions under risk," Journal of Risk and Uncertainty, Springer, vol. 64(3), pages 309-329, June.
    7. Sawa, Ryoji, 2021. "A prospect theory Nash bargaining solution and its stochastic stability," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 692-711.
    8. Carlos Alós-Ferrer & Jaume García-Segarra & Alexander Ritschel, 2018. "The Big Robber Game," ECON - Working Papers 291, Department of Economics - University of Zurich.
    9. Alós-Ferrer, Carlos & Ritschel, Alexander, 2021. "Multiple behavioral rules in Cournot oligopolies," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 250-267.

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    More about this item

    Keywords

    Reinforcement; Myopic best reply; Response times; Decision processes;
    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

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