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A model for the interaction of learning and evolution.

H Dopazo·M B Gordon·R Perazzo·S Risau-Gusman
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Abstract

We present a simple model in order to discuss the interaction of the genetic and behavioral systems throughout evolution. This considers a set of adaptive perceptrons in which some of their synapses can be updated through a learning process. This framework provides an extension of the well-known Hinton and Nowlan model by blending together some learning capability and other (rigid) genetic effects that contribute to the fitness. We find a halting effect in the evolutionary dynamics, in which the transcription of environmental data into genetic information is hindered by learning, instead of stimulated as is usually understood by the so-called Baldwin effect. The present results are discussed and compared with those reported in the literature. An interpretation is provided of the halting effect.

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AlgorithmsAllelesAnimalsBiological EvolutionGenotypeHumansLearningNeural Networks, ComputerNumerical Analysis, Computer-AssistedPhenotypeSynapsesComparative StudyJournal ArticleResearch Support, Non-U.S. Gov't

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H Dopazo, M B Gordon, R Perazzo, S Risau-Gusman. 2001. A model for the interaction of learning and evolution.. https://doi.org/10.1006/bulm.2000.0207

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