comp_pg_dfix_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运动模型（Markov movement model），对基于底层空间结构进行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，策略性地选择留在当前位置，或是迁移至邻近位置。本研究的基础是过往一项假设底层结构为完全图（complete graph，即本质上无结构）的研究。而本研究则考虑了其他类型的网络结构，并纳入了更多（主要为更大规模的）种群场景。过往研究发现，合作能否演化取决于一系列种群参数的取值。在本研究中，我们发现前述的完全图结构能够提升系统稳定性，合作者或背叛者种群相对难以被替换。与之形成对比的是，星型图（star graph）结构会加剧系统不稳定性，通常两类种群均无法抵御替换。我们将从网络拓扑（network topology）的角度，探讨产生这一差异的潜在原因。