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dc.contributor.authorFudenberg, Drew
dc.contributor.authorLevine, David K.
dc.date.accessioned2010-08-23T10:27:51Z
dc.date.issued2009
dc.identifier.citationFudenberg, Drew, and David K. Levine. 2009. Learning and equilibrium. Annual Review of Economics 1: 385–420.en_US
dc.identifier.issn1941-1383en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:4382413
dc.description.abstractThe theory of learning in games studies how, which and what kind of equilibria might arise as a consequence of a long-run non-equilibrium process of learning, adaptation and/or imitation. If agents’ strategies are completely observed at the end of each round, and agents are randomly matched with a series of anonymous opponents, fairly simple rules perform well in terms of the agent’s worst-case payoffs, and also guarantee that any steady state of the system must correspond to an equilibrium. If (as in extensive-form games) players do not observe the strategies chosen by their opponents, then learning is consistent with steady states that are not Nash equilibria because players can maintain incorrect beliefs about off-path play. Beliefs can also be incorrect due to cognitive limitations and systematic inferential errors.en_US
dc.description.sponsorshipEconomicsen_US
dc.language.isoen_USen_US
dc.publisherAnnual Reviewsen_US
dc.relation.isversionofdoi:10.1146/annurev.economics.050708.142930en_US
dash.licenseOAP
dc.subjectnon-equilibrium dynamicsen_US
dc.subjectbounded rationalityen_US
dc.subjectNash equilibriumen_US
dc.subjectselfconfirming equilibriumen_US
dc.titleLearning and Equilibriumen_US
dc.typeJournal Articleen_US
dc.description.versionAuthor's Originalen_US
dc.relation.journalAnnual Review of Economicsen_US
dash.depositing.authorFudenberg, Drew
dc.date.available2010-08-23T10:27:51Z
dc.identifier.doi10.1146/annurev.economics.050708.142930*
dash.contributor.affiliatedFudenberg, Drew


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