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Schemas and Genetic Programming

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Part of the book series: Studies in Cognitive Systems ((COGS,volume 26))

Abstract

To investigate the mechanisms which enable systems to learn is among the most challenging of research activities. In computer science alone it is pursued by at least three communities (Carbonel 1990; Natarajan 1991; Ritter et al. 1991). The overwhelming majority of all studies treats situations with strong inductive bias, i.e. there is a fairly narrow class H of algorithms and the concept or algorithm to be learned is known a priori to lie in that class H.

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© 2000 Springer Science+Business Media Dordrecht

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Birk, A., Paul, W.J. (2000). Schemas and Genetic Programming. In: Cruse, H., Dean, J., Ritter, H. (eds) Prerational Intelligence: Adaptive Behavior and Intelligent Systems Without Symbols and Logic, Volume 1, Volume 2 Prerational Intelligence: Interdisciplinary Perspectives on the Behavior of Natural and Artificial Systems, Volume 3. Studies in Cognitive Systems, vol 26. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0870-9_50

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  • DOI: https://doi.org/10.1007/978-94-010-0870-9_50

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-3792-1

  • Online ISBN: 978-94-010-0870-9

  • eBook Packages: Springer Book Archive

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