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Learning First Order Fuzzy Logic Rules

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Fuzzy Sets and Systems — IFSA 2003 (IFSA 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2715))

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Abstract

The paper presents an algorithm based on Inductive Logic Programming for inducing first order Horn clauses involving fuzzy predicates from a database. For this, a probabilistic processing of fuzzy function is used, in agreement with the handling of probabilities in first order logic. This technique is illustrated on an experimental application. The interest of learning fuzzy first order logic expressions is emphasized.

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Author information

Authors and Affiliations

  1. IRIT - Universite Paul Sabatier, 118 route de Narbonne, 31062, Toulouse, France

    Henri Prade, Gilles Richard & Mathieu Serrurier

Authors
  1. Henri Prade
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  2. Gilles Richard
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  3. Mathieu Serrurier
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Editor information

Editors and Affiliations

  1. Department of Industrial Engineering, Boğaziçi University, 34342, Bebek, Istanbul, Turkey

    Taner Bilgiç

  2. Dept. of Applied Mathematics, Biometrics and Process Control, Ghent University, Coupure links 653, 9000, Gent, Belgium

    Bernard De Baets

  3. Department of Electrical and Electronics Engineering, Boğaziçi University, 34342, Bebek, Istanbul, Turkey

    Okyay Kaynak

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© 2003 Springer-Verlag Berlin Heidelberg

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Prade, H., Richard, G., Serrurier, M. (2003). Learning First Order Fuzzy Logic Rules. In: Bilgiç, T., De Baets, B., Kaynak, O. (eds) Fuzzy Sets and Systems — IFSA 2003. IFSA 2003. Lecture Notes in Computer Science, vol 2715. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44967-1_84

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  • DOI: https://doi.org/10.1007/3-540-44967-1_84

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40383-8

  • Online ISBN: 978-3-540-44967-6

  • eBook Packages: Springer Book Archive

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