Combining classification and nonmonotonic inheritance reasoning: A first step

  • Lin Padgham
  • Bernhard Nebel
Logic for Artificial Intelligence II
Part of the Lecture Notes in Computer Science book series (LNCS, volume 689)


The formal analysis of semantic networks and frame systems led to the development of nonmonotonic inheritance networks and terminological logics. While nonmonotonic inheritance networks formalize the notion of default inheritance of typical properties, terminological logics formalize the notion of defining concepts and reasoning about definitions. Although it seems to be desirable to (re-)unify the two approaches, such an attempt has not been made until now. In this paper, we will make a first step into this direction by specifying a nonmonotonic extension of a simple terminological logic.


Semantic Network Default Reasoning Skeptical Theory Default Assumption Preference Labelling 
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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  1. 1.
    F. Baader and B. Hollunder. Embedding defaults into terminological knowledge representation formalisms. In Nebel et al. [9],. pages 306–317.Google Scholar
  2. 2.
    R. J. Brachman. 'I lied about the trees’ or, defaults and definitions in knowledge representation. The AI Magazine, 6(3):80–93, 1985.Google Scholar
  3. 3.
    J. Doyle and R. S. Patil. Two theses of knowledge representation: Language restrictions, taxonomic classification, and the utility of representation services. Artificial Intelligence, 48(3):261–298, Apr. 1991.Google Scholar
  4. 4.
    J. F. Horty and R. H. Thomason. Boolean extsionsins to inheritance networks. In Proceedings of the 8th National Conference of the American Association for Artificial Intelligence, pages 633–639, Boston, MA, Aug. 1990. MIT Press.Google Scholar
  5. 5.
    J. F. Horty, R. H. Thomason, and D. S. Touretzky. A skeptical theory of inheritance in nonmonotonic semantic networks. In Proceedings of the 6th National Conference of the American Association for Artificial Intelligence, pages 358–363, Seattle, WA, July 1987.Google Scholar
  6. 6.
    R. MacGregor. The evolving technology of classification-based knowledge representation systems. In J. F. Sowa, editor, Principles of Semantic Networks, pages 385–400. Morgan Kaufmann, San Mateo, CA, 1991.Google Scholar
  7. 7.
    D. Makinson and K. Schlechta. Floating conclusions and zombie paths: Two deep difficulties in the “directly skeptical” approach to defeasible inheritance nets. Artificial Intelligence, 48(2):199–211, Mar. 1991.Google Scholar
  8. 8.
    B. Nebel. Terminological reasoning is inherently intractable. Artificial Intelligence, 43:235–249, 1990.Google Scholar
  9. 9.
    B. Nebel, W. Swartout, and C. Rich, editors. Principles of Knowledge Representation and Reasoning: Proceedings of the 3rd International Conference, Cambridge, MA, Oct. 1992. Morgan Kaufmann.Google Scholar
  10. 10.
    L. Padgham. Non-Monotonic Inheritance for an Object-Oriented Knowledge Base. PhD thesis, University of Linköping, Linköping, Sweden, 1989. Linköping Studies in Science and Technology. Dissertations No. 213.Google Scholar
  11. 11.
    L. Padgham. Defeasible inheritance: A lattice based approach. Computers and Mathematics with Applications, 23(6–9):527–541, 1992. Special Issue on Semantic Nets.Google Scholar
  12. 12.
    P. F. Patel-Schneider, B. Owsnicki-Klewe, A. Kobsa, N. Guarino, R. MacGregor, W. S. Mark, D. McGuinness, B. Nebel, A. Schmiedel, and J. Yen. Term subsumption languages in knowledge representation. The AI Magazine, 11(2):16–23, 1990.Google Scholar
  13. 13.
    J. Quantz and V. Royer. A preference semantics for defaults in terminological logics. In Nebel et al. [9],. pages 294–305.Google Scholar
  14. 14.
    J. G. Schmolze and R. J. Brachman, editors. Proceedings of the 1981 KL-ONE Workshop, Cambridge, MA, 1982. Bolt, Beranek, and Newman Inc. BBN Report No. 4842.Google Scholar
  15. 15.
    T. Zhang and L. Padgham. A diagnosis system using inheritance in an inheritance net. In Proceedings of the Fifth International Symposium on Methodologies for Intelligent systems, Knoxville, TN, Oct. 1990. North-Holland.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Lin Padgham
    • 1
    • 2
  • Bernhard Nebel
    • 1
    • 2
  1. 1.Department of Computer and Information ScienceLinköping UniversityLinköpingSweden
  2. 2.German Research Center for Artificial Intelligence (DFKI)Saarbrücken 11Germany

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