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Understanding Cooperative Behavior Based on the Coevolution of Game Strategy and Link Weight

机译:基于博弈策略和链接权重的协同进化来了解合作行为

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摘要

In reality, the dependency relationship among individuals is heterogeneous and time-varying. Based on this fact, we present a new mechanism of coevolution of game strategy and link weight when analyzing the evolution of cooperation. In detail, we model the population on a regular network, on which the relationship between players is depicted by a weighted link, and prisoner’s dilemma has been applied to describe the interaction of players. Further, the impact of this mechanism on the cooperative behavior has been outlined. By conducting large-scale Monte Carlo simulations, we can easily draw a conclusion that this mechanism can promote cooperation efficiently. Compared with the traditional case, when the temptation of defection b is large, the fraction of cooperation is still able to keep in a high level. With a comprehensive examination of the distribution of stable link weight, it is evident that the coevolution mechanism would deviate the initial distribution. This mechanism induces the heterogeneity of players, which enhances the fraction of cooperation. Numerical simulations also indicate that an intermediate value of Δ/δ warrants an optimal resolution of prisoner’s dilemma. The mechanism of coevolution of game strategy and link weight has a practical significance and will provide new insight for the further research.
机译:实际上,个体之间的依赖关系是异质的并且随时间变化。基于这一事实,当分析合作的发展时,我们提出了一种新的博弈策略和链接权重协同进化的机制。详细而言,我们在常规网络上对人口进行建模,通过加权链接描绘玩家之间的关系,并采用囚徒困境来描述玩家之间的互动。此外,已经概述了该机制对合作行为的影响。通过进行大规模的蒙特卡洛模拟,我们可以轻松得出结论,该机制可以有效地促进合作。与传统情况相比,叛逃b的诱惑很大时,合作的比例仍然可以保持在较高水平。通过对稳定链路权重的分布进行全面检查,很明显协进化机制会偏离初始分布。这种机制导致参与者的异质性,从而增加了合作的比例。数值模拟还表明,Δ/δ的中间值可确保囚徒困境的最佳解决方案。博弈策略和链接权重的协同演化机制具有现实意义,将为进一步的研究提供新的见识。

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