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The expansion of neighborhood and pattern formation on spatial prisoner's dilemma

机译:空间囚徒困境的邻里扩展和模式形成

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The prisoner's dilemma (PD), in which players can either cooperate or defect, is considered a paradigm for studying the evolution of cooperation in spatially structured populations. There the compact cooperator cluster is identified as a characteristic pattern and the probability of forming such pattern in turn depends on the features of the networks. In this paper, we investigate the influence of expansion of neighborhood on pattern formation by taking a weak PD game with one free parameter T, the temptation to defect. Two different expansion methods of neighborhood are considered. One is based on a square lattice and expanses along four directions generating networks with degree increasing with K = 4m. The other is based on a lattice with Moore neighborhood and expanses along eight directions, generating networks with degree of K = 8m. Individuals are placed on the nodes of the networks, interact with their neighbors and learn from the better one. We find that cooperator can survive for a broad degree 4 <= K <= 70 by taking a loose type of cooperator clusters. The former simple corresponding relationship between macroscopic patterns and the microscopic PD interactions is broken. Under a condition that is unfavorable for cooperators such as large T and K, systems prefer to evolve to a loose type of cooperator clusters to support cooperation. However, compared to the well-known compact pattern, it is a suboptimal strategy because it cannot help cooperators dominating the population and always corresponding to a low cooperation level. (C) 2015 AIP Publishing LLC.
机译:玩家可以合作或叛逃的囚徒困境(PD)被认为是研究空间结构人口合作发展的范例。在那里,紧凑型合作者集群被识别为特征模式,而形成这种模式的可能性又取决于网络的特征。在本文中,我们通过采用带有一个自由参数T的弱PD博弈(缺陷的诱惑)来研究邻域扩展对图案形成的影响。考虑了两种不同的邻域扩展方法。一种是基于方格,并沿四个方向扩展,生成网络随着K = 4m的增加而增加。另一个基于具有摩尔邻域的晶格,并沿八个方向扩展,生成度为K = 8m的网络。个人被放置在网络的节点上,与邻居互动并向更好的人学习。我们发现,通过采用宽松类型的合作者集群,合作者可以在4 <= K <= 70的范围内生存。宏观模式与微观PD交互作用之间以前的简单对应关系被打破。在不利于大型T和K等合作者的条件下,系统倾向于演化为松散类型的合作者集群以支持合作。但是,与众所周知的紧凑模式相比,这是次优的策略,因为它无法帮助合作者控制人口并始终对应于较低的合作水平。 (C)2015 AIP Publishing LLC。

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