Selection of dynamical rules in spatial Prisoner's Dilemma games

被引:88
|
作者
Szabo, G. [1 ]
Szolnoki, A. [1 ]
Vukov, J. [1 ]
机构
[1] Res Inst Tech Phys & Mat Sci, H-1525 Budapest, Hungary
关键词
EVOLUTIONARY GAMES; LEARNING RULES; COOPERATION; STRATEGIES; NETWORKS; NOISE;
D O I
10.1209/0295-5075/87/18007
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
We study co-evolutionary Prisoner's Dilemma games where each player can imitate both the strategy and imitation rule from a randomly chosen neighbor with a probability dependent on the payoff difference when the player's income is collected from games with the neighbors. The players, located on the sites of a two-dimensional lattice, follow unconditional cooperation or defection and use individual strategy adoption rule described by a parameter. If the system is started from a random initial state then the present co-evolutionary rule drives the system towards a state where only one evolutionary rule remains alive even in the coexistence of cooperative and defective behaviors. The final rule is related to the optimum providing the highest level of cooperation and affected by the topology of the connectivity structure. Copyright (C) EPLA, 2009
引用
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页数:5
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