Department of Mathematics, University of London, London, United Kingdom.
Department of Mathematics and Statistics, University of North Carolina at Greensboro, Greensboro, NC, United States of America.
PLoS One. 2023 Aug 1;18(8):e0289366. doi: 10.1371/journal.pone.0289366. eCollection 2023.
Evolutionary models are used to study the self-organisation of collective action, often incorporating population structure due to its ubiquitous presence and long-known impact on emerging phenomena. We investigate the evolution of multiplayer cooperation in mobile structured populations, where individuals move strategically on networks and interact with those they meet in groups of variable size. We find that the evolution of multiplayer cooperation primarily depends on the network topology and movement cost while using different stochastic update rules seldom influences evolutionary outcomes. Cooperation robustly co-evolves with movement on complete networks and structure has a partially detrimental effect on it. These findings contrast an established principle from evolutionary graph theory that cooperation can only emerge under some update rules and if the average degree is lower than the reward-to-cost ratio and the network far from complete. We find that group-dependent movement erases the locality of interactions, suppresses the impact of evolutionary structural viscosity on the fitness of individuals, and leads to assortative behaviour that is much more powerful than viscosity in promoting cooperation. We analyse the differences remaining between update rules through a comparison of evolutionary outcomes and fixation probabilities.
进化模型被用于研究集体行动的自组织，由于其普遍存在且对新兴现象的长期影响，通常将种群结构纳入其中。我们研究了移动结构化群体中多人合作的进化，其中个体在网络上进行策略性移动，并与他们在不同大小的群体中遇到的个体进行互动。我们发现，多人合作的进化主要取决于网络拓扑结构和移动成本，而使用不同的随机更新规则很少会影响进化结果。合作与完整网络上的移动共同进化，而结构对其有部分不利影响。这些发现与进化图论中的一个既定原则相矛盾，即合作只能在某些更新规则下出现，如果平均度数低于奖励与成本的比值且网络远非完整。我们发现，依赖于群体的移动消除了相互作用的局部性，抑制了进化结构粘性对个体适应性的影响，并导致了比粘性更强大的聚集行为，从而促进了合作。我们通过比较进化结果和固定概率来分析不同更新规则之间的差异。
