How Can Evolution Learn?

被引:149
|
作者
Watson, Richard A. [1 ]
Szathmary, Eoers [2 ,3 ]
机构
[1] Univ Southampton, Inst Life Sci, Dept Comp Sci, Southampton SO17 1BJ, Hants, England
[2] Parmenides Fdn, Kirchpl 1, D-82049 Pullach Munich, Germany
[3] MTA ELTE Theoret Biol & Evolutionary Ecol Res Grp, Pazmany Peter Setany 1C, H-1117 Budapest, Hungary
基金
欧洲研究理事会;
关键词
SELECTION; ADAPTATION; TRANSITIONS; ECOSYSTEMS; COMMUNITY; NETWORKS; GENETICS; BIOLOGY; SYSTEMS;
D O I
10.1016/j.tree.2015.11.009
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
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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页码:147 / 157
页数:11
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