Computing Nash equilibria through computational intelligence methods

dc.contributor.authorPavlidis, N. G.en
dc.contributor.authorParsopoulos, K. E.en
dc.contributor.authorVrahatis, M. N.en
dc.date.accessioned2015-11-24T17:01:06Z
dc.date.available2015-11-24T17:01:06Z
dc.identifier.issn0377-0427-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/10872
dc.rightsDefault Licence-
dc.subjectnash equilibriaen
dc.subjectevolutionary algorithmsen
dc.subjectparticle swarrn optimizationen
dc.subjectdifferential evolutionen
dc.subjectevolulion strategyen
dc.subjectdifferential evolutionen
dc.subjectoptimizationen
dc.subjectadaptationen
dc.titleComputing Nash equilibria through computational intelligence methodsen
heal.abstractNash equilibrium constitutes a central solution concept in game theory. The task of detecting the Nash equilibria of a finite strategic game remains a challenging problem up-to-date. This paper investigates the effectiveness of three computational intelligence techniques, namely, covariance matrix adaptation evolution strategies, particle swarm optimization, as well as. differential evolution, to compute Nash equilibria of finite strategic games. as global minima of a real-valued, nonnegative function. An issue of particular interest is to detect more than one Nash equilibria of a game. The performance of the considered computational intelligence methods on this problem is investigated using multistart and deflection. (C) 2004 Elsevier B.V. All rights reserved.en
heal.accesscampus-
heal.fullTextAvailabilityTRUE-
heal.identifier.primaryDOI 10.1016/j.cam.2004.06.005-
heal.journalNameJournal of Computational and Applied Mathematicsen
heal.journalTypepeer reviewed-
heal.languageen-
heal.publicationDate2005-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Ηλεκτρονικών Υπολογιστών και Πληροφορικήςel
heal.typejournalArticle-
heal.type.elΆρθρο Περιοδικούel
heal.type.enJournal articleen

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