Zhang Yichao, Aziz-Alaoui M A, Bertelle Cyrille, Guan Jihong
1] Normandie Univ, France; ULH, LMAH, F-76600 Le Havre; FR-CNRS-3335, ISCN, 25 rue Ph. Lebon, 76600 Le Havre, France [2] Department of Computer Science and Technology, Tongji University, 4800 Cao'an Road, Shanghai 201804, China.
Normandie Univ, France; ULH, LMAH, F-76600 Le Havre; FR-CNRS-3335, ISCN, 25 rue Ph. Lebon, 76600 Le Havre, France.
Sci Rep. 2014 Aug 29;4:6224. doi: 10.1038/srep06224.
Nash equilibrium is widely present in various social disputes. As of now, in structured static populations, such as social networks, regular, and random graphs, the discussions on Nash equilibrium are quite limited. In a relatively stable static gaming network, a rational individual has to comprehensively consider all his/her opponents' strategies before they adopt a unified strategy. In this scenario, a new strategy equilibrium emerges in the system. We define this equilibrium as a local Nash equilibrium. In this paper, we present an explicit definition of the local Nash equilibrium for the two-strategy games in structured populations. Based on the definition, we investigate the condition that a system reaches the evolutionary stable state when the individuals play the Prisoner's dilemma and snow-drift game. The local Nash equilibrium provides a way to judge whether a gaming structured population reaches the evolutionary stable state on one hand. On the other hand, it can be used to predict whether cooperators can survive in a system long before the system reaches its evolutionary stable state for the Prisoner's dilemma game. Our work therefore provides a theoretical framework for understanding the evolutionary stable state in the gaming populations with static structures.
纳什均衡广泛存在于各种社会冲突之中。截至目前,在结构化静态群体中,如社交网络、规则图和随机图,关于纳什均衡的讨论相当有限。在相对稳定的静态博弈网络中,一个理性个体在采取统一策略之前,必须全面考虑其所有对手的策略。在这种情况下,系统中会出现一种新的策略均衡。我们将这种均衡定义为局部纳什均衡。在本文中,我们给出了结构化群体中双策略博弈的局部纳什均衡的明确定义。基于该定义,我们研究了个体进行囚徒困境博弈和雪堆博弈时系统达到进化稳定状态的条件。局部纳什均衡一方面提供了一种判断博弈结构化群体是否达到进化稳定状态的方法。另一方面,它可用于在系统达到囚徒困境博弈的进化稳定状态之前很久,预测合作者是否能在系统中生存。因此,我们的工作为理解具有静态结构的博弈群体中的进化稳定状态提供了一个理论框架。