Learning and Complexity in Genetic Auto-Adaptive Systems

Nonlinear Sciences – Adaptation and Self-Organizing Systems

Scientific paper

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27 p., tar-compressed uuencoded postscript incl. figures, subm. to "Complex Systems"

Scientific paper

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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