earticle

영어

Bargaining game analysis using metaheuristics has been drawing attention in recent years. This paper presents the interaction and co-evolutionary process between two kinds of metaheuristics-based agents, genetic algorithms (GA-based agent) and particle swarm optimization (PSO-based agent), in a bargaining game. Game performance with regard to payoff and deal rate through the interaction and co-evolution of agents is studied. The experimental results show that the PSO-based agent outperforms the GA-based agent in the bargaining game.