English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In evolutionary game dynamics, reproductive success increases with theperformance in an evolutionary game. If strategy $A$ performs better thanstrategy $B$, strategy $A$ will spread in the population. Under stochasticdynamics, a single mutant will sooner or later take over the entire populationor go extinct. We analyze the mean exit times (or average fixation times)associated with this process. We show analytically that these times depend onthe payoff matrix of the game in an amazingly simple way under weak selection,ie strong stochasticity: The payoff difference $\Delta \pi$ is a linearfunction of the number of $A$ individuals $i$, $\Delta \pi = u i + v$. Theunconditional mean exit time depends only on the constant term $v$. Given thata single $A$ mutant takes over the population, the corresponding conditionalmean exit time depends only on the density dependent term $u$. We demonstratethis finding for two commonly applied microscopic evolutionary processes.

Fixation times in evolutionary games under weak selection