Ifti Margarita, Killingback Timothy, Doebeli Michael
Department of Physics and Astronomy, University of British Columbia,Vancouver, BC, Canada V6T 1Z1.
J Theor Biol. 2004 Nov 7;231(1):97-106. doi: 10.1016/j.jtbi.2004.06.003.
The Prisoner's Dilemma, a two-person game in which the players can either cooperate or defect, is a common paradigm for studying the evolution of cooperation. In real situations cooperation is almost never all or nothing. This observation is the motivation for the Continuous Prisoner's Dilemma, in which individuals exhibit variable degrees of cooperation. It is known that in the presence of spatial structure, when individuals "play against" (i.e. interact with) their neighbours, and "compare to" ("learn from") them, cooperative investments can evolve to considerable levels. Here, we examine the effect of increasing the neighbourhood size: we find that the mean-field limit of no cooperation is reached for a critical neighbourhood size of about five neighbours on each side in a Moore neighbourhood, which does not depend on the size of the spatial lattice. We also find the related result that in a network of players, the critical average degree (number of neighbours) of nodes for which defection is the final state does not depend on network size, but only on the network topology. This critical average degree is considerably (about 10 times) higher for clustered (social) networks, than for distributed random networks. This result strengthens the argument that clustering is the mechanism which makes the development and maintenance of the cooperation possible. In the lattice topology, it is observed that when the neighbourhood sizes for "interacting" and "learning" differ by more than 0.5, cooperation is not sustainable, even for neighbourhood sizes that are below the mean-field limit of defection. We also study the evolution of neighbourhood sizes, as well as investment level. Here, we observe that the series of the interaction and learning neighbourhoods converge, and a final cooperative state with considerable levels of average investment is achieved.
囚徒困境是一种两人游戏,玩家可以选择合作或背叛,是研究合作进化的常见范式。在现实情况中,合作几乎从来不是全有或全无的。这一观察结果是连续囚徒困境的动机,在连续囚徒困境中,个体表现出不同程度的合作。众所周知,在存在空间结构的情况下,当个体与邻居“对抗”(即互动)并与他们“比较”(即“学习”)时,合作投资可以进化到相当高的水平。在这里,我们研究增加邻域大小的影响:我们发现在摩尔邻域中,每侧大约五个邻居的临界邻域大小会达到不合作的平均场极限,这与空间晶格的大小无关。我们还发现了相关结果,即在玩家网络中,背叛成为最终状态的节点的临界平均度(邻居数量)不取决于网络大小,而仅取决于网络拓扑。对于聚类(社交)网络,这个临界平均度比分布式随机网络高得多(约10倍)。这一结果强化了这样一种观点,即聚类是使合作得以发展和维持的机制。在晶格拓扑中,观察到当“互动”和“学习”的邻域大小差异超过0.5时,即使邻域大小低于背叛的平均场极限,合作也无法持续。我们还研究了邻域大小以及投资水平的演变。在这里,我们观察到互动和学习邻域的序列会收敛,并实现具有相当平均投资水平的最终合作状态。