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Stochastic gain in finite populations

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons56887

Röhl,  Torsten
Research Group Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons56973

Traulsen,  Arne
Department Evolutionary Ecology, Max Planck Institute for Evolutionary Biology, Max Planck Society;
Research Group Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Zitation

Röhl, T., Traulsen, A., Claussen, J. C., & Schuster, H. G. (2008). Stochastic gain in finite populations. Physical Review E, 78: 026108. doi:10.1103/PhysRevE.78.026108.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-D703-F
Zusammenfassung
Flexible learning rates can lead to increased payoffs under the influence of noise. In a previous paper [Traulsen et al., Phys. Rev. Lett. 93, 028701 (2004)], we have demonstrated this effect based on a replicator dynamics model which is subject to external noise. Here, we utilize recent advances on finite population dynamics and their connection to the replicator equation to extend our findings and demonstrate the stochastic gain effect in finite population systems. Finite population dynamics is inherently stochastic, depending on the population size and the intensity of selection, which measures the balance between the deterministic and the stochastic parts of the dynamics. This internal noise can be exploited by a population using an appropriate microscopic update process, even if learning rates are constant.