Sex as an algorithm the theory of evolution under the lens of computation

Adi Livnat, Christos Papadimitriou

Research output: Contribution to journalReview articlepeer-review

Abstract

Recent research at the interface of evolution and CS has revealed that evolution under sex possesses a surprising and multifaceted computational nature: It can be seen as a coordination game between genes played according to the powerful Multiplicative Weights Update Algorithm; or as a randomized algorithm for deciding whether genetic variants perform well across all possible genetic combinations; it allows mutation to process and transmit information from transient genetic combinations to future generations; and much more. Since sex breaks down genetic combinations, it has been mainly thought in evolution that effective selection acts on individual alleles, that is, each (non-neutral) allele is either beneficial or detrimental on its own. Sex enables evolution to sample quickly from the entire space of genetic combinations, in the distribution under which they appear in the population. What is more, evolution under sex not only decides among the competing hypotheses, but also implements this decision.

Original languageEnglish
Pages (from-to)84-93
Number of pages10
JournalCommunications of the ACM
Volume59
Issue number11
DOIs
StatePublished - Nov 2016

ASJC Scopus subject areas

  • General Computer Science

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