Sex with no regrets: how sexual reproduction uses a no regret learning algorithm for evolutionary advantage

DOI10.1016/j.jtbi.2017.05.018zbMath1381.92061OpenAlexW2616830022WikidataQ33365432 ScholiaQ33365432MaRDI QIDQ1702267

Dana Sherill-Rofe, Omer Edhan, Ziv Hellman

Publication date: 28 February 2018

Published in: Journal of Theoretical Biology (Search for Journal in Brave)

Full work available at URL: https://www.research.manchester.ac.uk/portal/en/publications/sex-with-no-regrets-how-sexual-reproduction-uses-a-no-regret-learning-algorithm-for-evolutionary-advantage(8839e34b-5f41-42a9-a6d0-df25bb958799).html

zbMATH Keywords

learning algorithmsevolutionsexual reproduction

Mathematics Subject Classification ID

Problems related to evolution (92D15) Genetics and epigenetics (92D10) Computational methods for problems pertaining to biology (92-08) Animal behavior (92D50)

Uses Software

• AdaBoost.MH

Cites Work

• Sam Karlin and the stochastic theory of evolutionary population genetics
• An interpretation and proof of the fundamental theorem of natural selection
• Cycling in simple genetic systems
• Towards a theory of the evolution of modifier genes
• A decision-theoretic generalization of on-line learning and an application to boosting
• On the evolutionary effect of recombination
• Algorithms, games, and evolution
• Hopf bifurcation in the two locus genetic model
• Stable cycling in discrete-time genetic models.
• Multiplicative updates outperform generic no-regret learning in congestion games
• On the nonexistence of adaptive topographies
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