Evolutionary dynamics on sequential temporal networks.

ABSTRACT: Population structure is a well-known catalyst for the evolution of cooperation and has traditionally been considered to be static in the course of evolution. Conversely, real-world populations, such as microbiome communities and online social networks, frequently show a progression from tiny, active groups to huge, stable communities, which is insufficient to be captured by constant structures. Here, we propose sequential temporal networks to characterize growing networked populations, and we extend the theory of evolutionary games to these temporal networks with arbitrary structures and growth rules. We derive analytical rules under which a sequential temporal network has a higher fixation probability for cooperation than its static counterpart. Under neutral drift, the rule is simply a f

SUBMITTER: Sheng A 

PROVIDER: S-EPMC10434888 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature