The Impact of Payoff Function and Local Interaction on the N-Player Iterated Prisoner's Dilemma

被引:22
作者
Yeon-Gyu Seo
Sung-Bae Cho
Xin Yao
机构
[1] Department of Computer Science,
[2] Yonsei University,undefined
[3] Seoul,undefined
[4] S. Korea,undefined
[5] School of Computer Science,undefined
[6] University of Birmingham,undefined
[7] Birmingham,undefined
[8] UK,undefined
关键词
Keywords: Co-evolutionary learning; Iterated prisoner's dilemma; Generalization; Local interaction;
D O I
10.1007/PL00011652
中图分类号
学科分类号
摘要
The N-player iterated prisoner's dilemma (NIPD) game has been widely used to study the evolution of cooperation in social, economic and biological systems. This paper studies the impact of different payoff functions and local interactions on the NIPD game. The evolutionary approach is used to evolve game-playing strategies starting from a population of random strategies. The different payoff functions used in our study describe different behaviors of cooperation and defection among a group of players. Local interaction introduces neighborhoods into the NIPD game. A player does not play against every other player in a group any more. He only interacts with his neighbors. We investigate the impact of neighborhood size on the evolution of cooperation in the NIPD game and the generalization ability of evolved strategies.
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页码:461 / 478
页数:17
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