starpg10_fast_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运动模型（Markov movement model），对依托底层空间结构开展互动的移动种群进行建模。种群间的互动以公共品博弈（public goods game）为载体，且支持任意规模的群体构成。个体将结合自身的探索策略与当前所在群体的组成结构，策略性地选择停留于当前位置，或是迁移至邻近位点。该建模框架基于此前的研究工作搭建，彼时的底层结构为完全图（complete graph，即实质上无空间结构）。本研究则拓展考量了其他类型的网络结构，以及覆盖范围更广、以较大种群为主的研究对象。既往研究表明，合作行为的演化能否发生，取决于一系列种群参数的取值。在本次研究中，我们发现前述的完全图结构能够提升种群稳定性，合作者或背叛者种群均相对难以被取代。与之相对，星型图（star graph）则会加剧种群不稳定性，两类种群均往往难以抵御被取代的结局。我们将从网络拓扑（network topology）的维度，探讨引发这一差异的潜在原因。