Christos A. Ioannou

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We propose a methodology that is generalizable to a broad class of repeated games in order to facilitate operability of belief learning models with repeated-game strategies. The methodology consists of (1) a generalized repeated-game strategy space, (2) a mapping between histories and repeated-game beliefs, and (3) asynchronous updating of repeated-game(More)
We examine the asymptotic behavior of a finite, but error-prone population, whose agents can choose one of ALLD (always defect), ALLC (always cooperate), or Pavlov (repeats the previous action if the opponent cooperated and changes action otherwise) to play the repeated Prisoner's Dilemma. A novelty of the study is that it allows for three types of errors(More)
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