How can evolution learn?
How can evolution learn?
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.
147-157
Watson, Richard
ce199dfc-d5d4-4edf-bd7b-f9e224c96c75
Szathmary, Eors
24149e74-bfce-43e0-ad61-4da6c811e765
February 2016
Watson, Richard
ce199dfc-d5d4-4edf-bd7b-f9e224c96c75
Szathmary, Eors
24149e74-bfce-43e0-ad61-4da6c811e765
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.
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e-pub ahead of print date: 17 December 2015
Published date: February 2016
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EEE
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Local EPrints ID: 396543
URI: http://eprints.soton.ac.uk/id/eprint/396543
ISSN: 0169-5347
PURE UUID: 206480d5-f12f-4cab-8014-60176b43b8ed
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Date deposited: 10 Jun 2016 12:47
Last modified: 15 Mar 2024 03:21
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Author:
Richard Watson
Author:
Eors Szathmary
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