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A commonly used assumption in evolutionary game theory is that natural selection acts on individuals in the same time scale; e.g., players use the same frequency to update their strategies. Variation in learning rates within populations suggests that evolutionary game theory may not necessarily be restricted to uniform time scales associated with the game interaction and strategy adaption evolution. In this study, we remove this restricting assumption by dividing the population into fast and slow groups according to the players' strategy updating frequencies and investigate how different strategy compositions of one group influence the evolutionary outcome of the other's fixation probabilities of strategies within its own group. Analytical analysis and numerical calculations are performed to study the evolutionary dynamics of strategies in typical classes of twoplayer games (prisoner's dilemma game, snowdrift game, and staghunt game). The introduction of the heterogeneity in strategyupdate time scales leads to substantial changes in the evolution dynamics of strategies. We provide an approximation formula for the fixation probability of mutant types in finite populations and study the outcome of strategy evolution under the weak selection. We find that although heterogeneity in time scales makes the collective evolutionary dynamics more complicated, the possible longrun evolutionary outcome can be effectively predicted under technical assumptions when knowing the population composition and payoff parameters.
Originele taal2  English 

Artikelnummer  032407 
Aantal pagina's  8 
Tijdschrift  Physical Review E 
Volume  94 
Nummer van het tijdschrift  3 
DOI's  
Status  Published  19sep2016 
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 1 Afgelopen

Evolution of selforganized division of labour
Weissing, F., Cao, M., Zhang, J., Boonekamp, J. & Elsner, D.
01/04/2014 → 01/03/2020
Project: Research