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The evolution of cooperation within the multigame environment based on the Particle Swarm Optimization algorithm
Affiliation:1. Economics and Management School, Wuhan University, Wuhan 430070, China;2. Institute of System and Engineer, Wuhan University, Wuhan 430070, China
Abstract:This paper studies the evolution of cooperation in a so-called multigame environment based on the Particle Swarm Optimization (PSO) algorithm. In a multigame environment, players use different game payoff matrices and acquire their utilities from their interactions with their neighbors. According to the PSO algorithm, each player updates its strategy according to both the strategy adopted by the player with the highest utility in its neighborhood and the most profitable strategy in their own past actions. Simulation results show that the multigame environment is conducive to the promotion of cooperation. Besides, within the multigame environment, for any player, imitating the most profitable strategy in its past actions promotes cooperation more effectively than imitating the strategy adopted by the player with the highest utility in its neighborhood.
Keywords:Multigame environment  Payoff matrix  Particle Swarm Optimization  Evolutionary game  Cooperation
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