LEARNING ACROSS GAMES

Friederike Mengel

Working Papers. Serie AD from Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie)

Abstract: In this paper (reinforcement) learning of decision makers that face many different games is studied. As learning separately for all games can be too costly (require too much reasoning resources) agents are assumed to partition the set of all games into analogy classes. 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. The model is able to explain deviations from subgame perfection that are sometimes observed in experiments even for vanishingly small reasoning costs. Furthermore it is shown that learning across games can stabilize mixed equilibria in 2×2 Coordination and Anti-Coordination games and destabilize strict Nash equilibria under certain conditions.

Keywords: Game Theory; Bounded Rationality; Reinforcement Learning; Analogies. (search for similar items in EconPapers)
JEL-codes: C70 C72 C73 (search for similar items in EconPapers)
Pages: 35 pages
Date: 2007-04
New Economics Papers: this item is included in nep-cbe and nep-gth
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Published by Ivie

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http://www.ivie.es/downloads/docs/wpasad/wpasad-2007-05.pdf Fisrt version / Primera version, 2007 (application/pdf)

Related works:
Journal Article: Learning across games (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:ivi:wpasad:2007-05

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