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Computing Nash equilibria through computational intelligence methods

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<mark>Journal publication date</mark>03/2005
<mark>Journal</mark>Journal of Computational and Applied Mathematics
Issue number1
Volume175
Number of pages24
Pages (from-to)113-136
Publication StatusPublished
<mark>Original language</mark>English

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.