Learning across games

F. Mengel

Research output: Contribution to journalArticleAcademicpeer-review

14 Citations (Scopus)

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 traveler's dilemma and deviations from subgame perfection in bargaining games. 

Original languageEnglish
Pages (from-to)601-619
Number of pages19
JournalGames and Economic Behavior
Volume74
Issue number2
DOIs
Publication statusPublished - Mar 2012

Keywords

  • Learning
  • Bounded rationality
  • Categorization
  • NORMAL-FORM GAMES
  • FICTITIOUS PLAY
  • EXTENSIVE-FORM
  • EQUILIBRIUM
  • MODELS
  • REINFORCEMENT

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