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 0377-0427Full text not available from this repository.
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.
|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|
|Departments:||Lancaster University Management School > Management Science|
|Deposited On:||09 Nov 2011 14:08|
|Last Modified:||29 Mar 2017 04:21|
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