Novel payoff calculation resolves social dilemmas in networks

Abstract

Standing in others’ shoes is usually describing the phenomenon that individuals switch their position and think about others’ benefits. This common saying can also stimulate the cooperation behavior, no matter in natural system or human society. In fact, Scholars have conducted abundant of researches to explore human behaviors in evolutionary game theory to discover how to improve cooperation among individualist. Results clearly showed that players can achieve the highest payoff when they choose cooperation strategy. However, selfishness among individuals results in that cooperation is not guaranteed every time, and how to improve cooperative behavior still remains a challenge in literature. Nevertheless, we analyzed the notion of “Standing in others’ shoes” through mathematical method, and analyzed this idea by introducing evolutionary game theory. The results indicate that the cooperation can be promoted significantly when players take opponents’ payoff into account. Here, a parameter of u was introduced into the simulation process representing when different strategies are applied by the focal player x and its neighbor, the focal player x will calculate its own payoff at possibilities u, and with the possibilities of 1−u considering its neighbor yi’s payoff. The Monte Carlo simulation is conducted on spatial-lattice network, BA scale-free network and small-world network respectively. The results reveal that the frequency of cooperation can be improved dramatically when parameter u reached a certain threshold.