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FMR: An Incremental Knowledge Acquisition System for Fuzzy Domains

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Knowledge Acquisition, Modeling and Management (EKAW 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1621))

Abstract

Ripple Down Rules (RDR) is an incremental Knowledge Acquisition (KA) technique that allows experts themselves to be in charge of performing the KA as well as the maintenance of the system. Although there are various real RDR approaches, fuzzy domain cannot be treated through RDR systems yet. The purpose of this work is to make use of the RDR advantages to construct fuzzy rule-based systems as well as to strengthen the utility of RDR in fuzzy domains. This aim has been achieved by introducing some assumptions relative to fuzzy domain modelling in combination with the construction of a new framework to manage and acquire (fuzzy) conclusions.

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References

  • Bouchon-Meunier B., (1992). Inferences with imprecisions and Uncertainties in Expert Systems, Fuzzy Expert Systems Theory, CRC Press.

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Author information

Authors and Affiliations

  1. Departmento de Inteligencia Artificial, Facultad de Informatica, Universidad de Murcia, Espinardo(Murcia), C. P.30071, Spain

    Rodrigo Martínez-Béjar & Francisca Ibáñez-Cruz

  2. Department of Artificial Intelligence, School of Computer Science and Engineering, The University of New South Wales, Sydney, 2052, NSW, Australia

    Thong Le-Gia, Tri M. Cao & Paul Compton

Authors
  1. Rodrigo Martínez-Béjar
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  2. Francisca Ibáñez-Cruz
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  3. Thong Le-Gia
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  4. Tri M. Cao
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  5. Paul Compton
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Editor information

Editors and Affiliations

  1. AIFB Institute for Applied Computer Science and Formal Description Methods, University of Karlsruhe, D-76128, Karlsruhe, Germany

    Dieter Fensel  & Rudi Studer  & 

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© 1999 Springer-Verlag

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Martínez-Béjar, R., Ibáñez-Cruz, F., Le-Gia, T., Cao, T.M., Compton, P. (1999). FMR: An Incremental Knowledge Acquisition System for Fuzzy Domains. In: Fensel, D., Studer, R. (eds) Knowledge Acquisition, Modeling and Management. EKAW 1999. Lecture Notes in Computer Science(), vol 1621. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48775-1_25

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  • DOI: https://doi.org/10.1007/3-540-48775-1_25

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66044-6

  • Online ISBN: 978-3-540-48775-3

  • eBook Packages: Springer Book Archive

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