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Learning and Complexity in Genetic Auto-Adaptive Systems

Chris Adami
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Abstract

We describe and investigate the learning capablities displayed by a population of self-replicating segments of computer-code subject to random mutation: the tierra environment. We find that learning is achieved through phase transitions that adapt the population to whichever environment it encounters, with a learning rate characterized by the environmental variables. Our results suggest that most effective learning is achieved close to the edge of chaos.

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Chris Adami. 1994-01-27. Learning and Complexity in Genetic Auto-Adaptive Systems. https://doi.org/10.1016/0167-2789(95)90073-x

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