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Strategies in the repeated prisoner’s dilemma: A cluster analysis

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  • Heller, Yuval
  • Tubul, Itay

Abstract

This study uses k-means clustering to analyze the strategic choices made by participants playing the infinitely repeated prisoner’s dilemma in laboratory experiments. We identify five distinct strategies that closely resemble well-known pure strategies: always defecting, suspicious tit-for-tat, grim, tit-for-tat, and always cooperating. Our analysis reveals moderate systematic deviations of the clustered strategies from their pure counterparts, and these deviations are important for capturing the experimental behavior. Additionally, we demonstrate that our approach significantly enhances the predictive power of previous analyses. Finally, we examine how the frequencies and payoffs of these clustered strategies vary based on the underlying game parameters.

Suggested Citation

  • Heller, Yuval & Tubul, Itay, 2023. "Strategies in the repeated prisoner’s dilemma: A cluster analysis," MPRA Paper 117444, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:117444
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    File URL: https://mpra.ub.uni-muenchen.de/117444/1/SRPD.pdf
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    More about this item

    Keywords

    k-means clustering; machine-learning; memory; laboratory experiment; repeated games.;
    All these keywords.

    JEL classification:

    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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    This paper has been announced in the following NEP Reports:

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