Coevolutionary dynamics in large, but finite populations

Details Coevolutionary dynamics in large, but finite populations Coevolutionary dynamics in large, but finite populations

2006-07-11

arxiv.org/abs/cond-mat/0607270v1

Physical Review E 74, 011901 (2006)

Physics

Condensed Matter

Statistical Mechanics

8 pages, 4 figs included

Scientific paper

10.1103/PhysRevE.74.011901

Coevolving and competing species or game-theoretic strategies exhibit rich and complex dynamics for which a general theoretical framework based on finite populations is still lacking. Recently, an explicit mean-field description in the form of a Fokker-Planck equation was derived for frequency-dependent selection with two strategies in finite populations based on microscopic processes [A.Traulsen, J.C. Claussen, and C.Hauert, Phys. Rev. Lett. 95, 238701 (2005)]. Here we generalize this approach in a twofold way: First, we extend the framework to an arbitrary number of strategies and second, we allow for mutations in the evolutionary process. The deterministic limit of infinite population size of the frequency dependent Moran process yields the adjusted replicator-mutator equation, which describes the combined effect of selection and mutation. For finite populations, we provide an extension taking random drift into account. In the limit of neutral selection, i.e. whenever the process is determined by random drift and mutations, the stationary strategy distribution is derived. This distribution forms the background for the coevolutionary process. In particular, a critical mutation rate $u_c$ is obtained separating two scenarios: above $u_c$ the population predominantly consists of a mixture of strategies whereas below $u_c$ the population tends to be in homogenous states. For one of the fundamental problems in evolutionary biology, the evolution of cooperation under Darwinian selection, we demonstrate that the analytical framework provides excellent approximations to individual based simulations even for rather small population sizes. This approach complements simulation results and provides a deeper, systematic understanding of coevolutionary dynamics.

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