Learning Fuzzy Decision Rules

  • Bernadette Bouchon-Meunier
  • Christophe Marsala
Part of the The Handbooks of Fuzzy Sets Series book series (FSHS, volume 5)


In this chapter a review of existing methods to learn fuzzy decision rules is done. Two kinds of learning methods exist. The first kind deals with the determination of the structure of the fuzzy decision rules. Fuzzy propositions (Vk is Ak) have to be chosen to compose premises and conclusions of such rules. The second kind of method is concerned with the tuning of the membership functions associated with the fuzzy propositions that appear in premises and conclusions of a given set of fuzzy decision rules.


Membership Function Fuzzy System Fuzzy Rule Fuzzy Decision Fuzzy Relational Equation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 1999

Authors and Affiliations

  • Bernadette Bouchon-Meunier
    • 1
  • Christophe Marsala
    • 1
  1. 1.LIP6Université Pierre et Marie Curie, Case 169Paris Cedex 5France

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