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通过与近邻分享收益来缓解社会困境。

Social dilemma alleviated by sharing the gains with immediate neighbors.

作者信息

Wu Zhi-Xi, Yang Han-Xin

机构信息

Institute of Computational Physics and Complex Systems, Lanzhou University, Lanzhou Gansu 730000, China.

Department of Physics, Fuzhou University, Fuzhou 350108, China.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2014 Jan;89(1):012109. doi: 10.1103/PhysRevE.89.012109. Epub 2014 Jan 9.

Abstract

We study the evolution of cooperation in the evolutionary spatial prisoner's dilemma game (PDG) and snowdrift game (SG), within which a fraction α of the payoffs of each player gained from direct game interactions is shared equally by the immediate neighbors. The magnitude of the parameter α therefore characterizes the degree of the relatedness among the neighboring players. By means of extensive Monte Carlo simulations as well as an extended mean-field approximation method, we trace the frequency of cooperation in the stationary state. We find that plugging into relatedness can significantly promote the evolution of cooperation in the context of both studied games. Unexpectedly, cooperation can be more readily established in the spatial PDG than that in the spatial SG, given that the degree of relatedness and the cost-to-benefit ratio of mutual cooperation are properly formulated. The relevance of our model with the stakeholder theory is also briefly discussed.

摘要

我们研究了进化空间囚徒困境博弈(PDG)和雪堆博弈(SG)中合作的演变,在这两种博弈中,每个玩家从直接博弈互动中获得的收益的一部分α由其直接邻居平均分享。因此,参数α的大小表征了相邻玩家之间的关联程度。通过广泛的蒙特卡罗模拟以及扩展的平均场近似方法,我们追踪了稳态下合作的频率。我们发现,引入关联可以在这两种研究的博弈背景下显著促进合作的演变。出乎意料的是,在关联程度和相互合作的成本效益比得到适当设定的情况下,空间PDG中比空间SG中更容易建立合作。我们还简要讨论了我们的模型与利益相关者理论的相关性。

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