International Institute for Applied Systems Analysis, Laxenburg, Austria.
BMC Evol Biol. 2010 Jun 11;10:173. doi: 10.1186/1471-2148-10-173.
Evolution of cooperative behaviour is widely studied in different models where interaction is heterogeneous, although static among individuals. However, in nature individuals can often recognize each other and chose, besides to cooperate or not, to preferentially associate with or to avoid certain individuals.Here we consider a dynamical interaction graph, in contrast to a static one. We propose several rules of rejecting unwanted partners and seeking out new ones, and study the probability of emergence and maintenance of cooperation on these dynamic networks.
Our simulations reveal that cooperation can evolve and be stable in the population if we introduce preferential linking, even if defectors can perform it too. The fixation of cooperation has higher probability than that of on static graphs, and this effect is more prevalent at high benefit to cost ratios. We also find an optimal number of partners, for which the fixation probability of cooperation shows a maximum.
The ability to recognize, seek out or avoid interaction partners based on the outcome of past interactions has an important effect on the emergence of cooperation. Observations about the number of partners in natural cooperating groups are in concordance with the result of our model.
合作行为的进化在不同的模型中得到了广泛的研究，这些模型中的个体间的相互作用是异质的，尽管个体之间的相互作用是静态的。然而，在自然界中，个体通常可以相互识别，并选择与某些个体优先关联或避免某些个体，而不仅仅是合作或不合作。在这里，我们考虑了一个动态的相互作用图，与静态图相反。我们提出了几种拒绝不想要的伙伴并寻找新伙伴的规则，并研究了在这些动态网络中合作的出现和维持的概率。
我们的模拟结果表明，如果我们引入优先链接，即使缺陷者也可以进行优先链接，合作也可以在种群中进化并保持稳定。与静态图相比，合作的固定具有更高的概率，并且这种效应在高收益成本比下更为普遍。我们还发现了一个最佳伙伴数量，在这个数量下，合作的固定概率达到最大值。
基于过去相互作用的结果来识别、寻求或避免相互作用伙伴的能力对合作的出现有重要影响。关于自然合作群体中伙伴数量的观察结果与我们模型的结果一致。
