Coevolutionary, coexisting learning and teaching agents model for prisoner's dilemma games enhancing cooperation with assortative heterogeneous networks

被引:27
|
作者
Tanimoto, Jun [1 ]
机构
[1] Kyushu Univ, Interdisciplinary Grad Sch Engn Sci, Kasuga, Fukuoka 8168580, Japan
关键词
Evolutionary game on network; Prisoner's dilemma game; Assortative coefficient; Coevolution; RECIPROCITY; EMERGENCE; EVOLUTION; STRATEGY;
D O I
10.1016/j.physa.2013.02.004
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Unlike other natural network systems, assortativity can be observed in most human social networks, although it has been reported that a social dilemma situation represented by the prisoner's dilemma favors dissortativity to enhance cooperation. We established a new coevolutionary model for both agents' strategy and network topology, where teaching and learning agents coexist. Remarkably, this model enables agents' enhancing cooperation more than a learners-only model on a time-frozen scale-free network and produces an underlying assortative network with a fair degree of power-law distribution. The model may imply how and why assortative networks are adaptive in human society. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:2955 / 2964
页数:10
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