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)
We use a genetic algorithm to simulate the evolution of error-prone finite automata in the repeated Prisoner's Dilemma game. In particular, the automata are subjected to implementation and perception errors. The computational experiments examine whether and how the distribution of outcomes and genotypes of the coevolved automata change with different levels(More)
Poisson games have been proposed to address equilibrium indeterminacy in Coordination games. They model the number of actual players as a Poisson random variable to capture population uncertainty in large games. Two natural questions are (a) whether uncertainty about the number of actual players does have an impact on subjects' behavior, and if so (b)(More)
We study experimentally the effect on individual behavior of comparative, but payoff-irrelevant, information in a near-minimal group setting. Specifically, in each round, group members see the groups' cumulative payoffs, which consist of an aggrega-tion of the earnings of each member of the group in the round. Our novel experimental design incorporates two(More)
A drawback of most adaptive learning models is that they only incorporate learning of stage-game actions rather than repeated-game strategies. Yet, evidence from the laboratory suggests that, in many games, subjects use repeated-game strategies. We modify the self-tuning Experience Weighted Attraction (EWA-lite) model of Camerer, Ho, and Chong (2007) and(More)
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