title: Crossover between structured and well-mixed networks in an evolutionary prisoner's dilemma game.
abstract: In a spatial evolutionary prisoner's dilemma game (PDG), individuals interact with their neighbors and update their strategies according to some rules. As is well known, cooperators are destined to become extinct in a well-mixed population, whereas they could emerge and be sustained on a structured network. In this work, we introduce a simple model to investigate the crossover between a structured network and a well-mixed one in an evolutionary PDG. In the model, each link j is designated a rewiring parameter τ(j), which defines the time interval between two successive rewiring events for link j. By adjusting the rewiring parameter τ (the mean time interval for any link in the network), we could change a structured network into a well-mixed one. For the link rewiring events, three situations are considered: one synchronous situation and two asynchronous situations. Simulation results show that there are three regimes of τ: large τ where the density of cooperators ρ(c) rises to ρ(c,∞) (the value of ρ(c) for the case without link rewiring), small τ where the mean-field description for a well-mixed network is applicable, and moderate τ where the crossover between a structured network and a well-mixed one happens.
authors.affiliation: School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China.
authors.forename: Qionglin
authors.initials: Q
authors.lastname: Dai
authors.forename: Hongyan
authors.initials: H
authors.lastname: Cheng
authors.forename: Haihong
authors.initials: H
authors.lastname: Li
authors.forename: Yuting
authors.initials: Y
authors.lastname: Li
authors.forename: Mei
authors.initials: M
authors.lastname: Zhang
authors.forename: Junzhong
authors.initials: J
authors.lastname: Yang
mesh_terms: D000465:Algorithms; D005075:Biological Evolution; D003198:Computer Simulation; D003299:Cooperative Behavior; D005716:Game Theory; D006801:Humans; D008954:Models, Biological; D008962:Models, Theoretical; D016012:Poisson Distribution