title: Population Fluctuation Promotes Cooperation in Networks.
abstract: We consider the problem of explaining the emergence and evolution of cooperation in dynamic network-structured populations. Building on seminal work by Poncela et al., which shows how cooperation (in one-shot prisoner's dilemma) is supported in growing populations by an evolutionary preferential attachment (EPA) model, we investigate the effect of fluctuations in the population size. We find that a fluctuating model - based on repeated population growth and truncation - is more robust than Poncela et al.'s in that cooperation flourishes for a wider variety of initial conditions. In terms of both the temptation to defect, and the types of strategies present in the founder network, the fluctuating population is found to lead more securely to cooperation. Further, we find that this model will also support the emergence of cooperation from pre-existing non-cooperative random networks. This model, like Poncela et al.'s, does not require agents to have memory, recognition of other agents, or other cognitive abilities, and so may suggest a more general explanation of the emergence of cooperation in early evolutionary transitions, than mechanisms such as kin selection, direct and indirect reciprocity.
authors.affiliation: University of Manchester, School of Computer Science - Machine Learning &Optimisation Group, UK.
authors.forename: Steve
authors.initials: S
authors.lastname: Miller
authors.affiliation: University of Manchester, School of Computer Science - Machine Learning &Optimisation Group, UK.
authors.forename: Joshua
authors.initials: J
authors.lastname: Knowles
mesh_terms: D003299:Cooperative Behavior; D005716:Game Theory; D006801:Humans; D008962:Models, Theoretical