Wu Zhi-Xi, Holme Petter
Department of Physics, Umeå University, 901 87 Umeå, Sweden.
Phys Rev E Stat Nonlin Soft Matter Phys. 2009 Aug;80(2 Pt 2):026108. doi: 10.1103/PhysRevE.80.026108. Epub 2009 Aug 10.
Spatial games are crucial for understanding patterns of cooperation in nature (and to some extent society). They are known to be more sensitive to local symmetries than, e.g., spin models. This paper concerns the evolution of the prisoner's dilemma game on regular lattices with three different types of neighborhoods--the von Neumann, Moore, and kagomé types. We investigate two kinds of dynamics for the players to update their strategies (that can be unconditional cooperator or defector). Depending on the payoff difference, an individual can adopt the strategy of a random neighbor [a voter-model-like dynamics (VMLD)] or impose its strategy on a random neighbor, i.e., invasion-process-like dynamics (IPLD). In particular, we focus on the effects of noise, in combination with the strategy dynamics, on the evolution of cooperation. We find that VMLD, compared to IPLD, better supports the spreading and sustaining of cooperation. We see that noise has nontrivial effects on the evolution of cooperation: maximum cooperation density can be realized either at a medium noise level, in the limit of zero noise or in both these regions. The temptation to defect and the local interaction structure determine the outcome. Especially, in the low noise limit, the local interaction plays a crucial role in determining the fate of cooperators. We elucidate these both by numerical simulations and mean-field cluster approximation methods.
空间博弈对于理解自然界(以及在某种程度上社会中的)合作模式至关重要。已知它们比例如自旋模型对局部对称性更敏感。本文关注在具有三种不同类型邻域(冯·诺依曼型、摩尔型和 kagomé 型)的规则晶格上囚徒困境博弈的演化。我们研究了玩家更新其策略(可以是无条件合作者或背叛者)的两种动力学。根据收益差异,个体可以采用随机邻居的策略[一种类似选民模型的动力学(VMLD)],或者将其策略强加给随机邻居,即类似入侵过程的动力学(IPLD)。特别地,我们关注噪声与策略动力学相结合对合作演化的影响。我们发现,与 IPLD 相比,VMLD 更有利于合作的传播和维持。我们看到噪声对合作演化有非平凡的影响:最大合作密度可以在中等噪声水平、零噪声极限或这两个区域都实现。背叛的诱惑和局部相互作用结构决定了结果。特别是,在低噪声极限下,局部相互作用在决定合作者的命运中起着关键作用。我们通过数值模拟和平均场簇近似方法阐明了这两者。