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Computing Nash equilibria through computational intelligence methods

Pavlidis, Nicos and Parsopoulos, Kostantinos E. and Vrahatis, Michael N. (2005) Computing Nash equilibria through computational intelligence methods. Journal of Computational and Applied Mathematics, 175 (1). pp. 113-136. ISSN 0377-0427

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Abstract

Nash 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.

Item Type: Article
Journal or Publication Title: Journal of Computational and Applied Mathematics
Uncontrolled Keywords: Nash equilibria ; Evolutionary algorithms Differential evolution; Evolution strategies ; Particle swarm optimization ; Differential evolution ; Evolution strategies
Subjects:
Departments: Lancaster University Management School > Management Science
ID Code: 50921
Deposited By: ep_importer_pure
Deposited On: 09 Nov 2011 14:08
Refereed?: Yes
Published?: Published
Last Modified: 26 Jul 2012 19:45
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/50921

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