Title of article :
Strategy selection in structured populations
Author/Authors :
Hisashi and Tarnita، نويسنده , , Corina E. and Ohtsuki، نويسنده , , Hisashi and Antal، نويسنده , , Tibor and Fu، نويسنده , , Feng and Nowak، نويسنده , , Martin A.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2009
Pages :
12
From page :
570
To page :
581
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 ( a c b d ) . We study a mutation and selection process. For weak selection strategy A is favored over B if and only if σ a + b > c + σ d . 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 :
Finite populations , Evolutionary dynamics , Stochastic effects
Journal title :
Journal of Theoretical Biology
Serial Year :
2009
Journal title :
Journal of Theoretical Biology
Record number :
1539785
Link To Document :
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