compg50_fast_cfix_T05.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物品博弈（public goods game）为形式，且可支持任意规模的群体。个体将基于自身的探索策略与当前群体构成，策略性地选择停留在当前位置，或是迁移至邻近位置。

本研究基于此前的研究工作拓展而来，彼时的底层交互结构为完全图（complete graph），即实际上不存在结构化限制。而在本次研究中，我们考量了多种替代网络结构，并针对更多样化（以大规模群体为主）的群体展开分析。

过往研究表明，合作行为的演化能否发生，取决于一系列群体参数的取值。在本次研究中，我们发现此前采用的完全图结构能够提升系统稳定性，合作者或背叛者群体均较难被替代。与之形成对照的是，星型图（star graph）结构则会加剧系统不稳定性，两类群体通常均无法抵御替代。最后，我们从网络拓扑（network topology）的视角，探讨了造成这一差异的潜在成因。