starpg50_fast_dfix.csv from The effect of network topology on optimal exploration strategies and the evolution of cooperation in a mobile population

We model a mobile population interacting over an underlying spatial structure using a Markov movement model. Interactions take the form of public goods games, and can feature an arbitrary group size. Individuals choose strategically to remain at their current location or to move to a neighbouring location, depending upon their exploration strategy and the current composition of their group. This builds upon previous work where the underlying structure was a complete graph (i.e. there was effectively no structure). Here, we consider alternative network structures and a wider variety of, mainly larger, populations. Previously, we had found when cooperation could evolve, depending upon the values of a range of population parameters. In our current work, we see that the complete graph considered before promotes stability, with populations of cooperators or defectors being relatively hard to replace. By contrast, the star graph promotes instability, and often neither type of population can resist replacement. We discuss potential reasons for this in terms of network topology.

我们采用马尔可夫移动模型（Markov movement model）对基于底层空间结构开展互动的移动群体进行建模，群体间的互动以公共品博弈（public goods games）的形式展开，且可设置任意规模的群体，个体将结合自身的探索策略与当前群体的组成情况，策略性地选择停留在当前位置，或是迁移至邻近位置。本研究基于此前的相关工作拓展而来，过往研究中底层互动结构为完全图（complete graph，即本质上不存在空间结构），而本次研究则考虑了多种替代型网络结构，同时纳入了规模更大、种类更为丰富的移动群体。过往相关研究表明，合作行为能否演化取决于一系列群体参数的具体取值，在本次研究中我们发现，此前研究所采用的完全图结构能够提升群体稳定性，合作者或背叛者构成的群体相对难以被取代，与之形成鲜明对比的是，星型网络（star graph）会加剧群体的不稳定性，两类群体往往都难以抵御被取代的风险，我们将从网络拓扑（network topology）的角度探讨造成这一差异的潜在原因。