Concept Logics

  • Franz Baader
  • Hans-Jürgen Bürckert
  • Bernhard Hollunder
  • Werner Nutt
  • Jörg H. Siekmann
Part of the ESPRIT Basic Research Series book series (ESPRIT BASIC)


Concept languages (as used in BACK, KL-ONE, KRYPTON, LOOM) are employed as knowledge representation formalisms in Artificial Intelligence. Their main purpose is to represent the generic concepts and the taxonomical hierarchies of the domain to be modeled. This paper addresses the combination of the fast taxonomical reasoning algorithms (e.g. subsumption, the classifier etc.) that come with these languages and reasoning in first order predicate logic. The interface between these two different modes of reasoning is accomplished by a new rule of inference, called constrained resolution. Correctness, completeness as well as the decidability of the constraints (in a restricted constraint language) are shown.


concept description languages KL-ONE constrained resolution taxonomical reasoning knowledge representation languages 


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Copyright information

© ECSC — EEC — EAEC, Brussels — Luxembourg 1990

Authors and Affiliations

  • Franz Baader
    • 1
  • Hans-Jürgen Bürckert
    • 1
  • Bernhard Hollunder
    • 1
  • Werner Nutt
    • 1
  • Jörg H. Siekmann
    • 2
  1. 1.Projektgruppe WINODFKI KaiserslauternKaiserslauternFR Germany
  2. 2.FB InformatikUniversität KaiserslauternKaiserslauternFR Germany

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