Literature DB >> 26705684

How Can Evolution Learn?

Richard A Watson1, Eörs Szathmáry2.   

Abstract

The theory of evolution links random variation and selection to incremental adaptation. In a different intellectual domain, learning theory links incremental adaptation (e.g., from positive and/or negative reinforcement) to intelligent behaviour. Specifically, learning theory explains how incremental adaptation can acquire knowledge from past experience and use it to direct future behaviours toward favourable outcomes. Until recently such cognitive learning seemed irrelevant to the 'uninformed' process of evolution. In our opinion, however, new results formally linking evolutionary processes to the principles of learning might provide solutions to several evolutionary puzzles - the evolution of evolvability, the evolution of ecological organisation, and evolutionary transitions in individuality. If so, the ability for evolution to learn might explain how it produces such apparently intelligent designs.
Copyright © 2015 Elsevier Ltd. All rights reserved.

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Year:  2015        PMID: 26705684     DOI: 10.1016/j.tree.2015.11.009

Source DB:  PubMed          Journal:  Trends Ecol Evol        ISSN: 0169-5347            Impact factor:   17.712


  42 in total

1.  Plastic responses to novel environments are biased towards phenotype dimensions with high additive genetic variation.

Authors:  Daniel W A Noble; Reinder Radersma; Tobias Uller
Journal:  Proc Natl Acad Sci U S A       Date:  2019-06-19       Impact factor: 11.205

Review 2.  The Cognitive Lens: a primer on conceptual tools for analysing information processing in developmental and regenerative morphogenesis.

Authors:  Santosh Manicka; Michael Levin
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-06-10       Impact factor: 6.237

Review 3.  Developmental Bias and Evolution: A Regulatory Network Perspective.

Authors:  Tobias Uller; Armin P Moczek; Richard A Watson; Paul M Brakefield; Kevin N Laland
Journal:  Genetics       Date:  2018-08       Impact factor: 4.562

Review 4.  Synthetic transitions: towards a new synthesis.

Authors:  Ricard Solé
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2016-08-19       Impact factor: 6.237

5.  Different perspectives on non-genetic inheritance illustrate the versatile utility of the Price equation in evolutionary biology.

Authors:  Heikki Helanterä; Tobias Uller
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2020-03-09       Impact factor: 6.237

Review 6.  The Ultimate Guide to Bacterial Swarming: An Experimental Model to Study the Evolution of Cooperative Behavior.

Authors:  Jinyuan Yan; Hilary Monaco; Joao B Xavier
Journal:  Annu Rev Microbiol       Date:  2019-06-10       Impact factor: 15.500

Review 7.  Adaptability and evolution.

Authors:  Patrick Bateson
Journal:  Interface Focus       Date:  2017-08-18       Impact factor: 3.906

8.  Variability in fitness effects can preclude selection of the fittest.

Authors:  Christopher J Graves; Daniel M Weinreich
Journal:  Annu Rev Ecol Evol Syst       Date:  2017-08-28       Impact factor: 13.915

9.  Probing complexity: thermodynamics and computational mechanics approaches to origins studies.

Authors:  Stuart J Bartlett; Patrick Beckett
Journal:  Interface Focus       Date:  2019-10-18       Impact factor: 3.906

10.  Simplification, Innateness, and the Absorption of Meaning from Context: How Novelty Arises from Gradual Network Evolution.

Authors:  Adi Livnat
Journal:  Evol Biol       Date:  2017-03-11       Impact factor: 3.119

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