circ_pg_bc_cfix.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.

我们使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）形式，且支持任意规模的群体。个体将依据自身的探索策略与当前群体的组成，策略性地选择留在当前位置，或是迁移至邻近位置。
本研究基于此前的相关工作拓展而来：此前的研究中，底层互动结构为完全图（complete graph，即本质上不存在空间结构）。本文则考量了多种替代网络结构，以及规模更大、类型更为多样的移动群体。过往研究表明，合作行为能否得以演化，取决于一系列群体参数的取值。
在本研究中，我们发现此前采用的完全图结构能够提升系统稳定性，由合作者或背叛者构成的群体均相对难以被替代。与之形成显著反差的是，星型图（star graph）会加剧系统的不稳定性，两类群体通常均难以抵御替代。我们将结合网络拓扑（network topology）特征，探讨引发这一差异的潜在原因。