Synergistic effects of self-optimization and imitation rules on the evolution of cooperation in the investor sharing game

Abstract

Mechanisms of diverse strategies have been introduced into evolutionary games recently. Among them, the aspiration payoff plays an important role in inner desires of individuals. Based on the ranking of neighbors’ highest payoffs, self-aspiration payoffs and self-current payoffs, a dynamic strategy updating rule reflecting the process of progressively pursuing higher payoffs is proposed to study the synergistic effects of inner desires and external environment on cooperation. The dynamic strategy updating rule includes local optima, imitation rule and self-optimization. We apply this updating method to the investor sharing game and conclude the level of cooperation increases under small aspiration levels. Through the simulation results, we find that self-optimization rule will increase the probability of defectors with high investment transforming into cooperators, who will promote the imitation of cooperation behaviors later. Meanwhile, both of the lower monopoly of markets and more random networks boost cooperation in groups. In addition, this dynamic nature of the strategy updating rule may provide an idea for studying mixing rules, multi-person games and the heterogeneity of individuals.