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dc.contributor.authorIzquierdo, Segismundo S.
dc.contributor.authorIzquierdo Millán, Luis Rodrigo 
dc.date.accessioned2015-09-16T11:28:03Z
dc.date.available2015-09-16T11:28:03Z
dc.date.issued2013-04
dc.identifier.issn0022-4715
dc.identifier.urihttp://hdl.handle.net/10259/3842
dc.description.abstractThis paper illustrates how a deterministic approximation of a stochastic process can be usefully applied to analyse the dynamics of many simple simulation models. To demonstrate the type of results that can be obtained using this approximation, we present two illustrative examples which are meant to serve as methodological references for researchers exploring this area. Finally, we prove some convergence results for simulations of a family of evolutionary games, namely, intra-population imitation models in n-player games with arbitrary payoffs.en
dc.description.sponsorshipMinisterio de Educación (JC2009- 00263), Ministerio de Ciencia e Innovación (CONSOLIDER-INGENIO 2010: CSD2010-00034, DPI2010-16920)en
dc.format.mimetypeapplication/pdf
dc.language.isoenges
dc.publisherSpringer Verlag (Germany)en
dc.relation.ispartofJournal of Statistical Physics. 2013, V. 151, n. 1, p. 254-276en
dc.subjectStochastic approximationen
dc.subjectMean dynamicen
dc.subjectMarkov modelsen
dc.subjectEvolutionary gamesen
dc.subject.otherGestión de empresases
dc.subject.otherIndustrial managementen
dc.titleStochastic Approximation to Understand Simple Simulation Modelsen
dc.typeinfo:eu-repo/semantics/article
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.relation.publisherversionhttp://dx.doi.org/10.1007/s10955-012-0654-z
dc.identifier.doi10.1007/s10955-012-0654-z
dc.relation.projectIDinfo:eu-repo/grantAgreement/MICINN/CSD2010-00034
dc.relation.projectIDinfo:eu-repo/grantAgreement/MICINN/DPI2010-16920
dc.relation.projectIDinfo:eu-repo/grantAgreement/MEC/JC2009-00263
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersionen


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