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

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Adi Livnat,

Christos PapadimitriouAuthors Info & Claims

Communications of the ACM, Volume 59, Issue 11

Pages 84 - 93

https://doi.org/10.1145/2934662

Published: 28 October 2016 Publication History

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Abstract

Looking at the mysteries of evolution from a computer science point of view yields some unexpected insights.

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Cohen IMarron A(2023)Evolution is driven by natural autoencoding: reframing species, interaction codes, cooperation and sexual reproductionProceedings of the Royal Society B: Biological Sciences10.1098/rspb.2022.2409290:1994Online publication date: Mar-2023
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Vardi M(2023)Resilience: The Key to Planetary and Societal SustainabilityIntroduction to Digital Humanism10.1007/978-3-031-45304-5_24(373-382)Online publication date: 21-Dec-2023
https://doi.org/10.1007/978-3-031-45304-5_24
Vardi M(2021)Efficiency vs. Resilience: Lessons from COVID-19Perspectives on Digital Humanism10.1007/978-3-030-86144-5_38(285-289)Online publication date: 24-Nov-2021
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Sex as an algorithm: the theory of evolution under the lens of computation
1. Applied computing
  1. Life and medical sciences

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Published In

Communications of the ACM Volume 59, Issue 11

November 2016

118 pages

ISSN:0001-0782

EISSN:1557-7317

DOI:10.1145/3013530

Editor:
Moshe Y. Vardi
Association for Computing Machinery, New York, NY

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 28 October 2016

Published in CACM Volume 59, Issue 11

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Cohen IMarron A(2023)Evolution is driven by natural autoencoding: reframing species, interaction codes, cooperation and sexual reproductionProceedings of the Royal Society B: Biological Sciences10.1098/rspb.2022.2409290:1994Online publication date: Mar-2023
https://doi.org/10.1098/rspb.2022.2409
Vardi M(2023)Resilience: The Key to Planetary and Societal SustainabilityIntroduction to Digital Humanism10.1007/978-3-031-45304-5_24(373-382)Online publication date: 21-Dec-2023
https://doi.org/10.1007/978-3-031-45304-5_24
Vardi M(2021)Efficiency vs. Resilience: Lessons from COVID-19Perspectives on Digital Humanism10.1007/978-3-030-86144-5_38(285-289)Online publication date: 24-Nov-2021
https://doi.org/10.1007/978-3-030-86144-5_38
Cohen IMarron A(2020)The evolution of universal adaptations of life is driven by universal properties of matter: energy, entropy, and interactionF1000Research10.12688/f1000research.24447.39(626)Online publication date: 2-Sep-2020
https://doi.org/10.12688/f1000research.24447.3
Cohen IMarron A(2020)The evolution of universal adaptations of life is driven by universal properties of matter: energy, entropy, and interactionF1000Research10.12688/f1000research.24447.29(626)Online publication date: 30-Jul-2020
https://doi.org/10.12688/f1000research.24447.2
Cohen IMarron A(2020)The evolution of universal adaptations of life is driven by universal properties of matter: energy, entropy, and interactionF1000Research10.12688/f1000research.24447.19(626)Online publication date: 18-Jun-2020
https://doi.org/10.12688/f1000research.24447.1
Catarci TMarrella ASantucci GSharf MVitaletti ADi Lucchio LImbesi LMalakuczi V(2020)From Consensus to Innovation. Evolving Towards Crowd-based User-Centered DesignInternational Journal of Human–Computer Interaction10.1080/10447318.2020.175333336:15(1460-1475)Online publication date: 28-Apr-2020
https://doi.org/10.1080/10447318.2020.1753333
Nguyen PSudholt D(2020)Memetic algorithms outperform evolutionary algorithms in multimodal optimisationArtificial Intelligence10.1016/j.artint.2020.103345(103345)Online publication date: Jun-2020
https://doi.org/10.1016/j.artint.2020.103345
Atiia AHopper CInoue KVidal SWaldispühl J(2020)Computational intractability law molds the topology of biological networksApplied Network Science10.1007/s41109-020-00268-05:1Online publication date: 24-Jun-2020
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Kaznatcheev A(2019)Computational Complexity as an Ultimate Constraint on EvolutionGenetics10.1534/genetics.119.302000212:1(245-265)Online publication date: 4-Mar-2019
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