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Comment
. 2014 Jul 22;111(29):10398-9.
doi: 10.1073/pnas.1410107111. Epub 2014 Jul 9.

Diverse forms of selection in evolution and computer science

Nicholas H Barton  1 , Sebastian Novak  2 , Tiago Paixão  2
Affiliations
Comment

Diverse forms of selection in evolution and computer science

Nicholas H Barton et al. Proc Natl Acad Sci U S A. .
No abstract available

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
(A) Allele frequencies change at a rate proportional to the gradient in mean fitness; on the arcsin-transformed scale used here (x = sin[θ/2]2) (8), the increase in mean fitness is maximized, given the distance moved. In this example, fitnesses of genotypes {0,0}, {0,1}, {1,0}, and {1,1} are 1, 0.97, 0.90, and 1.02, respectively. Thus, there are two stable equilibria, corresponding to peaks in the fitness landscape, with either {0,0} or {1,1} fixed. Black dots show a population that starts at {0.95, 0.02} (Lower Right), and evolves toward fixation of the {0,0} alleles over 300 generations. Contours of mean fitness are spaced at intervals 0.005. (B) In any generation, allele frequencies (black curve) maximize the sum of the cumulative fitness, U=∑jxit(j)Uit(j) and the entropy, S=−∑jxit(j)log[xit(j)]. As time proceeds, differences in U becomes larger, relative to the constant entropy, S, thus forcing allele frequencies toward fixation. This figure shows trajectories for the two genes.
See this image and copyright information in PMC

Comment on

  • Algorithms, games, and evolution.
    Chastain E, Livnat A, Papadimitriou C, Vazirani U. Chastain E, et al. Proc Natl Acad Sci U S A. 2014 Jul 22;111(29):10620-3. doi: 10.1073/pnas.1406556111. Epub 2014 Jun 16. Proc Natl Acad Sci U S A. 2014. PMID: 24979793 Free PMC article.

References

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