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dc.contributor.authorHuttegger, Simon*
dc.contributor.authorSkyrms, Brian*
dc.contributor.authorTarres, Pierre*
dc.contributor.authorWagner, Elliott*
dc.date.accessioned2016-01-21T15:41:26Z
dc.date.available2016-01-21T15:41:26Z
dc.date.issued2014
dc.identifier.issn0027-8424
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/15312
dc.language.isoenen
dc.subjectcostly signalingen
dc.subjectreplicator dynamicsen
dc.subjectMoran processen
dc.subject.ddc519en
dc.subject.classificationjelC.C7.C73en
dc.titleSome dynamics of signaling gamesen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenInformation transfer is a basic feature of life that includes signaling within and between organisms. Owing to its interactive nature, signaling can be investigated by using game theory. Game theoretic models of signaling have a long tradition in biology, economics, and philosophy. For a long time the analyses of these games has mostly relied on using static equilibrium concepts such as Pareto optimal Nash equilibria or evolutionarily stable strategies. More recently signaling games of various types have been investigated with the help of game dynamics, which includes dynamical models of evolution and individual learning. A dynamical analysis leads to more nuanced conclusions as to the outcomes of signaling interactions. Here we explore different kinds of signaling games that range from interactions without conflicts of interest between the players to interactions where their interests are seriously misaligned. We consider these games within the context of evolutionary dynamics (both infinite and finite population models) and learning dynamics (reinforcement learning). Some results are specific features of a particular dynamical model, whereas others turn out to be quite robust across different models. This suggests that there are certain qualitative aspects that are common to many real-world signaling interactions.en
dc.relation.isversionofjnlnameProceedings of the National Academy of Sciences of the United States of America
dc.relation.isversionofjnlvol111en
dc.relation.isversionofjnldate2014
dc.relation.isversionofjnlpages10873-10880en
dc.relation.isversionofdoi10.1073/pnas.1400838111en
dc.relation.isversionofjnlpublisherNational Academy of sciencesen
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.relation.forthcomingnonen
dc.relation.forthcomingprintnonen
dc.description.ssrncandidatenonen
dc.description.halcandidateouien
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewedoui
dc.relation.Isversionofjnlpeerreviewedouien
dc.date.updated2016-01-21T15:31:25Z
hal.person.labIds17255*
hal.person.labIds17255*
hal.person.labIds60*
hal.person.labIds83324*
hal.faultCode{"duplicate-entry":{"hal-01257517":{"doi":"1.0"}}}


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