Nash Equilibrium Computing Based on Deflective Memetic Algorithm

A BIO-inspired optimization algorithm named deflective Memetic algorithm for detecting multi-minima of multimodal functions is proposed. The Nash Equilibria detecting in game theory is used to test the proposed algorithm. The basic Memetic Algorithm is constructed of particle swarm optimization as global search and Tabu search as local search. Two improvements are incorporated to enhance PSO. Tabu search iterates through the neighborhood to get a local optimum. Deflective technique is incorporated to tune the search for multi minima. The performance is evaluated on a series of Nash Equilibria detecting examples. The results show that the deflective MA has a notable ability to detect multi minima while yielding high accuracy and performance.