Learning across games

Friederike Mengel

Games and Economic Behavior, 2012, vol. 74, issue 2, 601-619

Abstract: This paper studies the learning process carried out by two agents who are involved in many games. As distinguishing all games can be too costly (require too much reasoning resources) agents might partition the set of all games into categories. Partitions of higher cardinality are more costly. A process of simultaneous learning of actions and partitions is presented and equilibrium partitions and action choices characterized. Learning across games can destabilize strict Nash equilibria even for arbitrarily small reasoning costs and even if players distinguish all the games at the stable point. The model is also able to explain experimental findings from the travelerʼs dilemma and deviations from subgame perfection in bargaining games.

Keywords: Learning; Bounded rationality; Categorization (search for similar items in EconPapers)
JEL-codes: C70 C72 C73 (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (30)

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Related works:
Working Paper: LEARNING ACROSS GAMES (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:gamebe:v:74:y:2012:i:2:p:601-619

DOI: 10.1016/j.geb.2011.08.020

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