Archive-shared cooperative coevolutionary algorithm using Nash equilibria preservation
Haoyang Chen, Yasukuni Mori, Ikuo Matsuba · 2012
Cooperative Coevolutionary Algorithm (CCEA) has been widely applied to solve large scale and complex problems, which result in significant speedups over traditional genetic algorithm. However, CCEA do not search for the optimal solutions but the compromised solutions because of its nature of cooperation. So in the case that the object problem has infinite Nash equilibria, CCEA is expected to converge into suboptimal solution even employing the shared archive. In this paper, we propose a Nash equilibria preservation strategy which enables CCEA to jump out of the suboptimal solution and to keep searching without falling into the same suboptimal solutions found so far. The experiment results show that the capability of the archive-shared CCEA has been improved by using the proposed strategy, especially in dealing with problem having infinite Nash equilibria.