circ_pg_cfix_T25.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.

本研究采用马尔可夫移动模型（Markov movement model），对依托底层空间结构开展互动的移动群体进行建模。群体间的互动采用公共品博弈（public goods games）范式，且支持任意规模的群体。个体将结合自身的探索策略与当前所在群体的构成，策略性地选择停留于当前位置，或是迁移至邻近位置。本研究基于既往研究开展：既往研究中的底层结构为完全图（complete graph，即本质上无空间结构）。而本研究则探索了其他类型的网络结构，并将研究样本拓展至更多样化（以大规模群体为主）的研究对象。过往研究表明，合作行为能否演化，取决于一系列群体参数的取值。在本研究中，我们发现前述采用的完全图结构可提升系统稳定性，合作者群体与背叛者群体均相对难以被替代。与之形成对比的是，星型图结构则会加剧系统不稳定性，两类群体通常均无法抵御被替代的命运。我们将从网络拓扑（network topology）的视角，探讨造成这一差异的潜在原因。