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Conditional constraints, implication based rules, and possibilistic rule bases: are they any good?

Weisbrod, Joachim; Spott, Martin


To answer the question imposed in the title right away: Yes,
they are. Conditional constraints, implication based rules, and
possibilistic rule bases are different notions representing the
very same concept. And this concept is as useful and interesting
as the well known and widely used Mamdani approach. So far, real
success in applying fuzzy rule bases is restricted to fuzzy
control and Mamdani inference. We claim that the lack of
applications making use of possibilistic reasoning is mainly due
to a lack of understanding how to deal with rules based on
possibility distributions.

Mamdani inference as used in fuzzy control and possibilistic
reasoning are complementary mechanisms. They are complementary
with respect to the way they deal with incomplete and
inconsistent information. From that point of view, it is not
surprising that using the very same rule base in both settings
does not work. This means, that the standard way of specifying
Mamdani knowledge bases does not help in the possibilistic case.
Based on the assumption that rule based systems are helpful and
manageable as long as rules represent local information we
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DOI: 10.5445/IR/4122000
Cover der Publikation
Zugehörige Institution(en) am KIT Universität Karlsruhe (TH) – Einrichtungen in Verbindung mit der Universität (Einrichtungen in Verbindung mit der Universität)
Forschungszentrum Informatik, Karlsruhe (FZI)
Institut für Programmstrukturen und Datenorganisation (IPD)
Publikationstyp Forschungsbericht/Preprint
Publikationsjahr 2000
Sprache Englisch
Identifikator ISSN: 1432-7864
KITopen-ID: 4122000
Verlag Universität Karlsruhe (TH)
Serie Interner Bericht. Fakultät für Informatik, Universität Karlsruhe ; 2000,23
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