2012
DOI: 10.1186/1471-2148-12-160
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The impact of random frequency-dependent mutations on the average population fitness

Abstract: BackgroundIn addition to selection, the process of evolution is accompanied by stochastic effects, such as changing environmental conditions, genetic drift and mutations. Commonly it is believed that without genetic drift, advantageous mutations quickly fixate in a halpoid population due to strong selection and lead to a continuous increase of the average fitness. This conclusion is based on the assumption of constant fitness. However, for frequency dependent fitness, where the fitness of an individual depends… Show more

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Cited by 13 publications
(12 citation statements)
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“…In this paper we have shown that a heuristic approach, based on the assumption of the existence of a scaling factor, can provide a way to make analytic conclusions without specifying any precise form for the distribution of mutations. Interestingly, a similar observation has been made for a game theoretic model of the evolution of average population fitness [45], although the analytic form of the observed scaling function was distinct. An important avenue for further investigations will be to determine if this approach can be used to as a general method for addressing problems involving stochastic mutation events.…”
Section: Discussionsupporting
confidence: 72%
“…In this paper we have shown that a heuristic approach, based on the assumption of the existence of a scaling factor, can provide a way to make analytic conclusions without specifying any precise form for the distribution of mutations. Interestingly, a similar observation has been made for a game theoretic model of the evolution of average population fitness [45], although the analytic form of the observed scaling function was distinct. An important avenue for further investigations will be to determine if this approach can be used to as a general method for addressing problems involving stochastic mutation events.…”
Section: Discussionsupporting
confidence: 72%
“…In order to determine how frequent such rank changes occur or how generic these games are, we analyze changes in the ranking of strategies in random games [36] [39] . In particular, we compute the probability that rank changes occur and determine the number of changes in the rank of strategies, see Figure 3 .…”
Section: Resultsmentioning
confidence: 99%
“…Naturally this also holds for games with more strategies. To determine the probability and numbers of such rank changes in random games [36] [39] , we generalize the numerical procedure described above.…”
Section: Resultsmentioning
confidence: 99%
“…We define the fitness of a strategy S as f S = exp[wπ S ] [29]. We follow the usual assumption that mutations only switch between the pre-existing strategies but do not generate an entirely novel strategy; for such a model we refer to [30][31][32]. The non-negative parameter w measures the intensity of selection [33].…”
Section: Introductionmentioning
confidence: 99%