Instability of Defection in the Prisoner’s Dilemma: Best Experienced Payoff Dynamics Analysis

Srinivas Arigapudi, Yuval Heller and Igal Milchtaich

MPRA Paper from University Library of Munich, Germany

Abstract: We study population dynamics under which each revising agent tests each strategy k times, with each trial being against a newly drawn opponent, and chooses the strategy whose mean payoff was highest. When k = 1, defection is globally stable in the prisoner’s dilemma. By contrast, when k > 1 we show that there exists a globally stable state in which agents cooperate with probability between 28% and 50%. Next, we characterize stability of strict equilibria in general games. Our results demonstrate that the empirically-plausible case of k > 1 can yield qualitatively different predictions than the case of k = 1 that is commonly studied in the literature.

Keywords: learning; cooperation; best experienced payoff dynamics; sampling equilibrium; evolutionary stability (search for similar items in EconPapers)
JEL-codes: C72 C73 (search for similar items in EconPapers)
Date: 2020-04-11
New Economics Papers: this item is included in nep-evo, nep-gth and nep-mic
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https://mpra.ub.uni-muenchen.de/99594/1/MPRA_paper_99594.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/99843/2/MPRA_paper_99843.pdf revised version (application/pdf)
https://mpra.ub.uni-muenchen.de/104424/1/MPRA_paper_104424.pdf revised version (application/pdf)
https://mpra.ub.uni-muenchen.de/105079/1/MPRA_paper_105079.pdf revised version (application/pdf)

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