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Observation of Bargaining Game using Co-evolution between Particle Swarm Optimization and Differential Evolution

입자군집최적화와 차분진화알고리즘 간의 공진화를 활용한 교섭게임 관찰

  • 이상욱 (목원대학교 정보통신융합공학부)
  • Received : 2014.10.08
  • Accepted : 2014.10.27
  • Published : 2014.11.28

Abstract

Recently, analysis of bargaining game using evolutionary computation is essential issues in field of game theory. In this paper, we observe a bargaining game using co-evolution between two heterogenous artificial agents. In oder to model two artificial agents, we use a particle swarm optimization and a differential evolution. We investigate algorithm parameters for the best performance and observe that which strategy is better in the bargaining game under the co-evolution between two heterogenous artificial agents. Experimental simulation results show that particle swarm optimization outperforms differential evolution in the bargaining game.

Keywords

Bargaining Game;Particle Swarm Optimization;Differential Evolution;Co-evolution

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