How Fuzzy Is My Fuzzy Description Logic?

  • Stefan Borgwardt
  • Felix Distel
  • Rafael Peñaloza
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7364)

Abstract

Fuzzy Description Logics (DLs) with t-norm semantics have been studied as a means for representing and reasoning with vague knowledge. Recent work has shown that even fairly inexpressive fuzzy DLs become undecidable for a wide variety of t-norms. We complement those results by providing a class of t-norms and an expressive fuzzy DL for which ontology consistency is linearly reducible to crisp reasoning, and thus has its same complexity. Surprisingly, in these same logics crisp models are insufficient for deciding fuzzy subsumption.

Keywords

Description Logic Zero Divisor Residual Negation Fuzzy Ontology Existential Restriction 
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-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Stefan Borgwardt
    • 1
  • Felix Distel
    • 1
  • Rafael Peñaloza
    • 1
  1. 1.Theoretical Computer ScienceTU DresdenGermany

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