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International Conference on Parallel Problem Solving from Nature

PPSN 2002: Parallel Problem Solving from Nature — PPSN VII pp 485–494Cite as

Automatic Recurrent and Feed-Forward ANN Rule and Expression Extraction with Genetic Programming

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2439))

Abstract

Various rule-extraction techniques using ANN have been used so far, most of them being applied on multi-layer ANN, since they are more easily handled. In many cases, extraction methods focusing on different types of networks and training have been implemented. However, there are virtually no methods that view the extraction of rules from ANN as systems which are independent from their architecture, training and internal distribution of weights, connections and activation functions. This paper proposes a ruleextraction system of ANN regardless of their architecture (multi-layer or recurrent), using Genetic Programming as a rule-exploration technique.

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Author information

Authors and Affiliations

  1. Facultad Informática, Univ. da Coruña, Campus Elviña, 15071, A Coruña, Spain

    Julian Dorado, Juan R. Rabuñal, Antonino Santos, Alejandro Pazos & Daniel Rivero

Authors
  1. Julian Dorado
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  2. Juan R. Rabuñal
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  3. Antonino Santos
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  4. Alejandro Pazos
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  5. Daniel Rivero
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Editor information

Editors and Affiliations

  1. Escuela Técnica Superior de Ingeniería Informática, 18071, Granada, Spain

    Juan Julián Merelo Guervós

  2. Department of Informatics, Technological Educational Institute of Thessaloniki, 54101, Thessaloniki, Greece

    Panagiotis Adamidis

  3. Department of Informatics XI, University of Dortmund, 44221, Dortmund, Germany

    Hans-Georg Beyer  & Hans-Paul Schwefel  & 

  4. Department of Signal Theory and Communications, Universidad Carlos III, Madrid, Spain

    José-Luis Fernández-Villacañas

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© 2002 Springer-Verlag Berlin Heidelberg

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Dorado, J., Rabuñal, J.R., Santos, A., Pazos, A., Rivero, D. (2002). Automatic Recurrent and Feed-Forward ANN Rule and Expression Extraction with Genetic Programming. In: Guervós, J.J.M., Adamidis, P., Beyer, HG., Schwefel, HP., Fernández-Villacañas, JL. (eds) Parallel Problem Solving from Nature — PPSN VII. PPSN 2002. Lecture Notes in Computer Science, vol 2439. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45712-7_47

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  • DOI: https://doi.org/10.1007/3-540-45712-7_47

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44139-7

  • Online ISBN: 978-3-540-45712-1

  • eBook Packages: Springer Book Archive

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