Emergence Of Cooperation On Complex Networks Based On Aspiration Payoff And Teamwork

Evolutionary game theory furnishes a strong theoretical framework for the emergence of cooperation.Complex network,together with the evolutionary game,forms the network reciprocity,one of the mechanisms to explain the emergence of cooperation.Based on these backgrounds,this paper studies the aspiration-based strategy update mechanism and the teamwork-based compromise game model on complex networks.Firstly,a dynamic strategy updating rule including includes local optima,imitation rule and self-optimization is proposed.Then,this paper simulates the investor sharing game on WS smallworld networks by using this updating method,and concludes that the level of cooperation increases under small aspiration levels.What's more,both the lower monopoly of markets and more random networks bring more cooperators in groups.This strategy updating rule may provide an idea for studying mixing rules,multi-person games and the heterogeneity of individuals.Secondly,this paper proposes a dynamic interaction strategy to determine interactive neighbors based on aspiration payoffs.Under this strategy,interactions only happen among the same level individuals.Based on the the prisoner's dilemma game on a square lattice,the simulations show that the introduction of this interaction strategy successfully delays the extinction of cooperators.And the appropriate aspiration level leads to a state of complete cooperation.Thirdly,considering the appearance of psychological game during the process of reaching a consensus on cooperators' decisions in reality,and based on the effects of environments on the thinking way of individuals,this paper proposes a compromise game and explores the evolution of compromise during the process of reaching agreement on BA scale-free networks with varying assortativity coefficient.Results show that individuals with high abilities tend to insist on themselves,and the compromise is closely related to the environment.