Title
Invasion of cooperation in scale-free networks: Accumulated vs. average payoffs
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.
Year
DOI
Venue
2017
10.1162/ARTL_a_00220
Artificial Life
Keywords
Field
DocType
Evolution of cooperation,evolutionary game,fitness function,invasion dynamics,prisoner's dilemma,scale-free network
Population,Evolutionarily stable strategy,Computer science,Simulation,Microeconomics,Prisoner's dilemma,Fitness function,Scale-free network,Artificial intelligence,Evolutionary dynamics,Stochastic game
Journal
Volume
Issue
ISSN
23
1
1064-5462
Citations 
PageRank 
References 
6
0.58
4
Authors
2
Name
Order
Citations
PageRank
Genki Ichinose1295.80
Hiroki Sayama231949.14