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The Structure of Mutations and the Evolution of Cooperation

Overview of attention for article published in PLOS ONE, April 2012
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Title
The Structure of Mutations and the Evolution of Cooperation
Published in
PLOS ONE, April 2012
DOI 10.1371/journal.pone.0035287
Pubmed ID
Authors

Julián García, Arne Traulsen

Abstract

Evolutionary game dynamics in finite populations assumes that all mutations are equally likely, i.e., if there are n strategies a single mutation can result in any strategy with probability 1/n. However, in biological systems it seems natural that not all mutations can arise from a given state. Certain mutations may be far away, or even be unreachable given the current composition of an evolving population. These distances between strategies (or genotypes) define a topology of mutations that so far has been neglected in evolutionary game theory. In this paper we re-evaluate classic results in the evolution of cooperation departing from the assumption of uniform mutations. We examine two cases: the evolution of reciprocal strategies in a repeated prisoner's dilemma, and the evolution of altruistic punishment in a public goods game. In both cases, alternative but reasonable mutation kernels shift known results in the direction of less cooperation. We therefore show that assuming uniform mutations has a substantial impact on the fate of an evolving population. Our results call for a reassessment of the "model-less" approach to mutations in evolutionary dynamics.

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Mendeley readers

The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 3%
Japan 1 2%
Philippines 1 2%
Belgium 1 2%
Unknown 61 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 24%
Researcher 12 18%
Student > Bachelor 9 14%
Student > Doctoral Student 5 8%
Student > Master 5 8%
Other 14 21%
Unknown 5 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 35%
Physics and Astronomy 10 15%
Computer Science 5 8%
Mathematics 3 5%
Medicine and Dentistry 3 5%
Other 14 21%
Unknown 8 12%