Adaptation and complexity in repeated games
Research output: Contribution to journal › Journal article › Research › peer-review
The paper presents a learning model for two-player infinitely repeated games. In an inference step players construct minimally complex inferences of strategies based on observed play, and in an adaptation step players choose minimally complex best responses to an inference. When players randomly select an inference from a probability distribution with full support the set of steady states is a subset of the set of Nash equilibria in which only stage game Nash equilibria are played. When players make ‘cautious' inferences the set of steady states is the subset of self-confirming equilibria with Nash outcome paths. When players use different inference rules, the set of steady states can lie between the previous two cases
Original language | English |
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Journal | Games and Economic Behavior |
Volume | 63 |
Issue number | 1 |
Pages (from-to) | 166-187 |
Number of pages | 22 |
ISSN | 0899-8256 |
DOIs | |
Publication status | Published - 2008 |
- Faculty of Social Sciences - learning, bounded rationality
Research areas
ID: 1847349