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Strategy selection in structured populations
Authors:Corina E. Tarnita  Hisashi Ohtsuki  Tibor Antal  Feng Fu  Martin A. Nowak
Affiliation:a Program for Evolutionary Dynamics, Department of Mathematics, Harvard University, Cambridge, MA 02138, USA
b Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
c Department of Value and Decision Science, Tokyo Institute of Technology, Tokyo 152-8552, Japan
d PRESTO, Japan Science and Technology Agency, Saitama 332-0012, Japan
e Center for Systems and Control, State Key Laboratory for Turbulence and Complex Systems, College of Engineering, Peking University, Beijing 100871, China
Abstract:
Evolutionary game theory studies frequency dependent selection. The fitness of a strategy is not constant, but depends on the relative frequencies of strategies in the population. This type of evolutionary dynamics occurs in many settings of ecology, infectious disease dynamics, animal behavior and social interactions of humans. Traditionally evolutionary game dynamics are studied in well-mixed populations, where the interaction between any two individuals is equally likely. There have also been several approaches to study evolutionary games in structured populations. In this paper we present a simple result that holds for a large variety of population structures. We consider the game between two strategies, A and B, described by the payoff matrix View the MathML source. We study a mutation and selection process. For weak selection strategy A is favored over B if and only if σa+b>c+σd. This means the effect of population structure on strategy selection can be described by a single parameter, σ. We present the values of σ for various examples including the well-mixed population, games on graphs, games in phenotype space and games on sets. We give a proof for the existence of such a σ, which holds for all population structures and update rules that have certain (natural) properties. We assume weak selection, but allow any mutation rate. We discuss the relationship between σ and the critical benefit to cost ratio for the evolution of cooperation. The single parameter, σ, allows us to quantify the ability of a population structure to promote the evolution of cooperation or to choose efficient equilibria in coordination games.
Keywords:Evolutionary dynamics   Finite populations   Stochastic effects
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