The impact of preferential selection mechanism based on average payoff and stability of payoff on the evolution of cooperation

Abstract

Recent studies on memory-based cooperative evolution have focused on random selection of learning objects and only considered average payoff, neglecting stability of payoff. Here, we propose a preference selection mechanism adopting the TOPSIS method, a multi-attribute decision-making approach. We introduce the weighting factors ω 1 and ω 2, which refer to average payoff and stability of payoff, respectively. The probability that an individual select his neighbor is influenced by both average payoff and stability. We investigate the effect of memory length M and ω 1 on the evolution of cooperation. The simulation results indicate that M and ω 1 can both somewhat promote cooperation. Given that , for small betrayal temptation b, cooperation is more robust for small M, while for large b, large values of M are preferred. Further exploring the impact of ω 1, for relatively small b, the influence of ω 1 on cooperation is gradually revealed and strengthened as M increases. Conversely, for relatively large b, the impact of ω 1 on cooperation slowly diminishes from strong as M increase, reflecting a gradual rise in the importance of stability. These findings enhance the understanding of cooperative behavior in real social environments and make more rational decisions under the multi-factor evaluation based on average payoff and stability.