dc.contributor.author | FUDENBERG, Drew | |
dc.contributor.author | LEVINE, David K. | |
dc.date.accessioned | 2019-03-01T14:53:25Z | |
dc.date.available | 2019-03-01T14:53:25Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | Journal of economic perspectives, 2016, Vol. 30, No.4, pp. 151-170 | |
dc.identifier.issn | 0895-3309 | |
dc.identifier.issn | 1944-7965 | en |
dc.identifier.uri | https://hdl.handle.net/1814/61465 | |
dc.description.abstract | Game theory has been a huge success in economics. Many important questions have been answered, and game theoretic methods are now central to much economic investigation. We suggest areas where further advances are important, and argue that models of learning are a promising route for improving and widening game theory's predictive power while preserving the successes of game theory where it already works well. We emphasize in particular the need for better understanding of the speed with which learning takes place. | |
dc.language.iso | en | |
dc.publisher | American Psychological Association | en |
dc.relation.ispartof | Journal of economic perspectives | |
dc.subject | Normal-Form Games | en |
dc.subject | Infinitely Repeated Games | en |
dc.subject | Equilibrium Selection | en |
dc.subject | Public Information | en |
dc.subject | Folk Theorem | en |
dc.subject | Cooperation | en |
dc.subject | Evolution | en |
dc.subject | Dynamics | en |
dc.subject | Models | en |
dc.subject | Supergames | en |
dc.title | Whither game theory? : towards a theory of learning in games | |
dc.type | Article | |
dc.identifier.doi | 10.1257/jep.30.4.151 | |
dc.identifier.volume | 30 | |
dc.identifier.startpage | 151 | |
dc.identifier.endpage | 170 | |
eui.subscribe.skip | true | |
dc.identifier.issue | 4 | |