KI - Künstliche Intelligenz

, Volume 31, Issue 1, pp 85–90 | Cite as

Decidability and Complexity of Fuzzy Description Logics

  • Franz Baader
  • Stefan BorgwardtEmail author
  • Rafael Peñaloza
Research Project


Fuzzy description logics (FDLs) have been introduced to represent concepts for which membership cannot be determined in a precise way, i.e., where instead of providing a strict border between being a member and not being a member, it is more appropriate to model a gradual change from membership to non-membership. First approaches for reasoning in FDLs where based either on a reduction to reasoning in classical description logics (DLs) or on adaptations of reasoning approaches for DLs to the fuzzy case. However, it turned out that these approaches in general do not work if expressive terminological axioms, called general concept inclusions (GCIs), are available in the FDL. The goal of this project was a comprehensive study of the border between decidability and undecidability for FDLs with GCIs, as well as determining the exact complexity of the decidable logics. As a result, we have provided an almost complete classification of the decidability and complexity of FDLs with GCIs.


Knowledge representation and reasoning Vagueness Fuzzy Description Logics 



This report describes the outcome of the project Reasoning in Fuzzy Description Logics with General Concept Inclusion Axioms (FuzzyDL) funded by the German Research Foundation (DFG) grant BA 1122/17-1. We are indebted to Felix Distel, Marco Cerami, Theofilos Mailis, and Anni-Yasmin Turhan for many discussions and contributions.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Franz Baader
    • 1
  • Stefan Borgwardt
    • 1
    Email author
  • Rafael Peñaloza
    • 2
  1. 1.Theoretical Computer ScienceTU DresdenDresdenGermany
  2. 2.KRDB Research CentreFU Bozen-BolzanoBolzanoItaly

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