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Title:
Algorithms, games, and evolution
Authors:
Chastain, Erick; Livnat, Adi; Papadimitriou, Christos; Vazirani, Umesh
Affiliation:
AA(Computer Science Department, Rutgers University, Piscataway, NJ 08854), AB(Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24061), AC(Computer Science Division, University of California, Berkeley, CA, 94720), AD(Computer Science Division, University of California, Berkeley, CA, 94720)
Publication:
Proceedings of the National Academy of Sciences, Volume 111, Issue 29, 2014, pp.10620-10623
Publication Date:
07/2014
Origin:
CROSSREF; PNAS
DOI:
10.1073/pnas.1406556111
Bibliographic Code:
2014PNAS..11110620C

Abstract

Even the most seasoned students of evolution, starting with Darwin himself, have occasionally expressed amazement that the mechanism of natural selection has produced the whole of Life as we see it around us. There is a computational way to articulate the same amazement: "What algorithm could possibly achieve all this in a mere three and a half billion years?" In this paper we propose an answer: We demonstrate that in the regime of weak selection, the standard equations of population genetics describing natural selection in the presence of sex become identical to those of a repeated game between genes played according to multiplicative weight updates (MWUA), an algorithm known in computer science to be surprisingly powerful and versatile. MWUA maximizes a tradeoff between cumulative performance and entropy, which suggests a new view on the maintenance of diversity in evolution.
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