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oai:riubu.ubu.es:10259/38422024-05-13T10:37:50Zcom_10259_3830com_10259_5086com_10259_2604col_10259_3832

Izquierdo, Segismundo S. Izquierdo Millán, Luis Rodrigo 2015-09-16T11:28:03Z 2015-09-16T11:28:03Z 2013-04 0022-4715 http://hdl.handle.net/10259/3842 10.1007/s10955-012-0654-z This 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. Ministerio de Educación (JC2009- 00263), Ministerio de Ciencia e Innovación (CONSOLIDER-INGENIO 2010: CSD2010-00034, DPI2010-16920) application/pdf eng Springer Verlag (Germany) Journal of Statistical Physics. 2013, V. 151, n. 1, p. 254-276 http://dx.doi.org/10.1007/s10955-012-0654-z info:eu-repo/grantAgreement/MICINN/CSD2010-00034 info:eu-repo/grantAgreement/MICINN/DPI2010-16920 info:eu-repo/grantAgreement/MEC/JC2009-00263 Stochastic approximation Mean dynamic Markov models Evolutionary games Gestión de empresas Industrial management Stochastic Approximation to Understand Simple Simulation Models info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion info:eu-repo/semantics/openAccess