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Extrapolating Weak Selection in Evolutionary Games

Overview of attention for article published in PLoS Computational Biology, December 2013
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Title
Extrapolating Weak Selection in Evolutionary Games
Published in
PLoS Computational Biology, December 2013
DOI 10.1371/journal.pcbi.1003381
Pubmed ID
Authors

Bin Wu, Julián García, Christoph Hauert, Arne Traulsen

Abstract

In evolutionary games, reproductive success is determined by payoffs. Weak selection means that even large differences in game outcomes translate into small fitness differences. Many results have been derived using weak selection approximations, in which perturbation analysis facilitates the derivation of analytical results. Here, we ask whether results derived under weak selection are also qualitatively valid for intermediate and strong selection. By "qualitatively valid" we mean that the ranking of strategies induced by an evolutionary process does not change when the intensity of selection increases. For two-strategy games, we show that the ranking obtained under weak selection cannot be carried over to higher selection intensity if the number of players exceeds two. For games with three (or more) strategies, previous examples for multiplayer games have shown that the ranking of strategies can change with the intensity of selection. In particular, rank changes imply that the most abundant strategy at one intensity of selection can become the least abundant for another. We show that this applies already to pairwise interactions for a broad class of evolutionary processes. Even when both weak and strong selection limits lead to consistent predictions, rank changes can occur for intermediate intensities of selection. To analyze how common such games are, we show numerically that for randomly drawn two-player games with three or more strategies, rank changes frequently occur and their likelihood increases rapidly with the number of strategies [Formula: see text]. In particular, rank changes are almost certain for [Formula: see text], which jeopardizes the predictive power of results derived for weak selection.

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Geographical breakdown

Country Count As %
United States 1 4%
Netherlands 1 4%
Unknown 26 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 32%
Professor 3 11%
Researcher 3 11%
Student > Postgraduate 2 7%
Student > Master 1 4%
Other 3 11%
Unknown 7 25%
Readers by discipline Count As %
Mathematics 5 18%
Social Sciences 3 11%
Agricultural and Biological Sciences 3 11%
Biochemistry, Genetics and Molecular Biology 2 7%
Physics and Astronomy 2 7%
Other 5 18%
Unknown 8 29%