Literature DB >> 28140631

Invasion of Cooperation in Scale-Free Networks: Accumulated versus Average Payoffs.

Genki Ichinose1, Hiroki Sayama2.   

Abstract

It is well known that cooperation cannot be an evolutionarily stable strategy for a non-iterative game in a well-mixed population. In contrast, structured populations favor cooperation, since cooperators can benefit each other by forming local clusters. Previous studies have shown that scale-free networks strongly promote cooperation. However, little is known about the invasion mechanism of cooperation in scale-free networks. To study microscopic and macroscopic behaviors of cooperators' invasion, we conducted computational experiments on the evolution of cooperation in scale-free networks where, starting from all defectors, cooperators can spontaneously emerge by mutation. Since the evolutionary dynamics are influenced by the definition of fitness, we tested two commonly adopted fitness functions: accumulated payoff and average payoff. Simulation results show that cooperation is strongly enhanced with the accumulated payoff fitness compared to the average payoff fitness. However, the difference between the two functions decreases as the average degree increases. As the average degree increases, cooperation decreases for the accumulated payoff fitness, while it increases for the average payoff fitness. Moreover, for the average payoff fitness, low-degree nodes play a more important role in spreading cooperative strategies than for the accumulated payoff fitness.

Keywords:  Evolution of cooperation; evolutionary game; fitness function; invasion dynamics; prisoner's dilemma; scale-free network

Mesh:

Year:  2017        PMID: 28140631     DOI: 10.1162/ARTL_a_00220

Source DB:  PubMed          Journal:  Artif Life        ISSN: 1064-5462            Impact factor:   0.667


  1 in total

1.  Research on an evolutionary game model and simulation of a cluster innovation network based on fairness preference.

Authors:  Chuanyun Li; Xia Cao; Ming Chi
Journal:  PLoS One       Date:  2020-01-13       Impact factor: 3.240

  1 in total

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