Algorithms, games, and evolution

Erick Chastain; Adi Livnat; Christos PapadimitriouUmesh Vazirani

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Algorithms, games, and evolution

机译：Algorithms, games, and evolution

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Even the most seasoned students of evolution, startingwith 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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《Proceedings of the National Academy of Sciences of the United States of America》 |2014年第29期|10620-10623|共4页
作者
Erick Chastain; Adi Livnat; Christos PapadimitriouUmesh Vazirani;
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作者单位

Computer Science Department, Rutgers University, Piscataway, NJ 08854;

Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24061;

Computer Science Division, University of California, Berkeley, CA, 94720;

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收录信息美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
原文格式 PDF
正文语种英语
中图分类自然科学总论;
关键词
coordination games; learning algorithms;

Algorithms, games, and evolution

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