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基于博弈策略与链路权重协同进化理解合作行为。

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

作者信息

Huang Keke, Zheng Xiaoping, Li Zhijie, Yang Yeqing

机构信息

Department of Automation, Tsinghua University, Beijing 100084, China.

出版信息

Sci Rep. 2015 Oct 5;5:14783. doi: 10.1038/srep14783.

Abstract

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.

摘要

实际上,个体之间的依赖关系是异质且随时间变化的。基于这一事实,我们在分析合作演化时提出了一种博弈策略与链路权重共同演化的新机制。具体而言,我们在规则网络上对群体进行建模,网络中参与者之间的关系由加权链路描述,并且应用囚徒困境来描述参与者之间的互动。此外,还概述了该机制对合作行为的影响。通过进行大规模蒙特卡罗模拟,我们很容易得出结论,该机制能够有效地促进合作。与传统情况相比,当背叛诱惑b较大时,合作比例仍能保持在较高水平。通过全面考察稳定链路权重的分布,很明显共同演化机制会偏离初始分布。该机制引发了参与者的异质性,从而提高了合作比例。数值模拟还表明,Δ/δ的中间值保证了囚徒困境的最优解。博弈策略与链路权重的共同演化机制具有实际意义,并将为进一步研究提供新的见解。

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