Neighbourhood reaction in the evolution of cooperation.
Combining evolutionary games with adaptive networks, an entangled model between strategy evolution and structure adaptation is researched in this paper. We consider a large population of cooperators C and defectors D placed in the networks, playing the repeated prisoner׳s dilemma (PD) games. Because of the conflicts between social welfare and personal rationality, both strategy and structure are allowed to change. In this paper, the dynamics of strategy originates form the partner imitation based on social learning and the dynamics of structure is driven by the active linking and neighbourhood reaction. Notably, the neighbourhood reaction is investigated considering the changes of interfaces between cooperators and defectors, where some neighbours may get away from the interface once the focal agent changes to different strategy. A rich landscape is demonstrated by changing various embedding parameters, which sheds light upon that reacting promptly to the shifted neighbour will promote the prevalence of cooperation. Our model encapsulates the dynamics of strategy, reaction and structure into the evolutionary games, which manifests some intriguing principles in the competition between two groups in natural populations, artificial systems and even human societies.
School of Informatics, University of Edinburgh, EH8 9AB, United Kingdom; College of Information System and Management, NUDT, Changsha 410073, China. Electronic address: yangguoli@nudt.edu.cn.
Guoli
G
Yang
College of Information System and Management, NUDT, Changsha 410073, China.
Weiming
W
Zhang
College of Information System and Management, NUDT, Changsha 410073, China.
Baoxin
B
Xiu
D000465:Algorithms; D000818:Animals; D005075:Biological Evolution; D003198:Computer Simulation; D003299:Cooperative Behavior; D006801:Humans; D007398:Interpersonal Relations; D008954:Models, Biological; D011157:Population Dynamics; D000068956:Prisoner Dilemma; D011336:Probability; D012919:Social Behavior; D012946:Social Welfare
Adaptive networks; Evolutionary games; Neighbourhood reaction