Department of Computer Science/Institute for Life Sciences, University of Southampton, Highfield, Southampton, SO17 1BJ, UK.
The Parmenides Foundation, Kirchplatz 1, 82049, Pullach/Munich, Germany; MTA-ELTE Theoretical Biology and Evolutionary Ecology Research Group, Pázmány Péter sétány 1C, Budapest 1117, Hungary.
Trends Ecol Evol. 2016 Feb;31(2):147-157. doi: 10.1016/j.tree.2015.11.009. Epub 2015 Dec 17.
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.
进化理论将随机变异和选择与渐进式适应联系起来。在不同的知识领域，学习理论将渐进式适应（例如，来自正强化和/或负强化）与智能行为联系起来。具体来说，学习理论解释了渐进式适应如何从过去的经验中获取知识，并利用这些知识指导未来的行为，以获得有利的结果。直到最近，这种认知学习似乎与进化的“无信息”过程无关。然而，我们认为，将进化过程与学习原则正式联系起来的新结果可能为解决几个进化难题提供解决方案——可进化性的进化、生态组织的进化以及个体的进化转变。如果是这样，进化的学习能力可能解释了它如何产生如此明显的智能设计。
