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社会惩罚对复杂网络中合作行为的影响。

Impact of social punishment on cooperative behavior in complex networks.

作者信息

Wang Zhen, Xia Cheng-Yi, Meloni Sandro, Zhou Chang-Song, Moreno Yamir

机构信息

1] Department of Physics, Hong Kong Baptist University, Kowloon Tong, Hong Kong [2] Center for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Center for Nonlinear and Complex systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong.

出版信息

Sci Rep. 2013 Oct 28;3:3055. doi: 10.1038/srep03055.

Abstract

Social punishment is a mechanism by which cooperative individuals spend part of their resources to penalize defectors. In this paper, we study the evolution of cooperation in 2-person evolutionary games on networks when a mechanism for social punishment is introduced. Specifically, we introduce a new kind of role, punisher, which is aimed at reducing the earnings of defectors by applying to them a social fee. Results from numerical simulations show that different equilibria allowing the three strategies to coexist are possible as well as that social punishment further enhance the robustness of cooperation. Our results are confirmed for different network topologies and two evolutionary games. In addition, we analyze the microscopic mechanisms that give rise to the observed macroscopic behaviors in both homogeneous and heterogeneous networks. Our conclusions might provide additional insights for understanding the roots of cooperation in social systems.

摘要

社会惩罚是一种机制,通过这种机制,合作个体花费部分资源来惩罚背叛者。在本文中,我们研究了在引入社会惩罚机制时,二人网络进化博弈中合作行为的演变。具体而言,我们引入了一种新的角色——惩罚者,其目的是通过向背叛者收取社会费用来减少他们的收益。数值模拟结果表明,三种策略共存的不同均衡是可能的,并且社会惩罚进一步增强了合作的稳健性。我们的结果在不同的网络拓扑结构和两种进化博弈中都得到了证实。此外,我们分析了在同质性和异质性网络中导致观察到的宏观行为的微观机制。我们的结论可能为理解社会系统中合作的根源提供更多见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b6d8/3808815/37d5b1aef4c3/srep03055-f1.jpg

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