Computing Nash equilibria through computational intelligence methods

  • Authors:

  • N. G. Pavlidis;K. E. Parsopoulos;M. N. Vrahatis

  • Affiliations:

  • Department of Mathematics, University of Patras Artificial Intelligence Center (UPAIRC), University of Patras, GR 26110 Patras, Greece;Department of Mathematics, University of Patras Artificial Intelligence Center (UPAIRC), University of Patras, GR 26110 Patras, Greece;Department of Mathematics, University of Patras Artificial Intelligence Center (UPAIRC), University of Patras, GR 26110 Patras, Greece

  • Venue:
  • Journal of Computational and Applied Mathematics - Special issue: Selected papers of the international conference on computational methods in sciences and engineering (ICCMSE-2003)
  • Year:
  • 2005

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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.