Computing Nash equilibria through computational intelligence methods

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

卷:175

Article; Proceedings Paper

Pavlidis, NG ; Parsopoulos, KE ; Vrahatis, MN

关键词: Nash equilibria;    evolutionary algorithms;    particle swarrn optimization;    differential evolution;    evolulion strategy;   

DOI  :  10.1016/j.cam.2004.06.005

来源: Elsevier

【 摘 要 】

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. (C) 2004 Elsevier B.V. All rights reserved.

【 授权许可】

Free