Possibilistic logic: From nonmonotonicity to logic programming

  • Salem Benferhat
  • Didier Dubois
  • Henri Prade
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 747)


Links between preferential semantics of possibilistic logic, semantics of prioritized circumscription, and one of the semantics used in logic programming, namely the perfect model semantics of stratified logic programs, are presented.


Logic Program Logic Programming Perfect Model Possibility Distribution Possibilistic Logic 
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  1. [Apt et al., 1988]
    K. Apt, H. Blair, A. Walker, Towards a Theory of Declarative knowledge, in: Foundation of Deductive Databases and Logic Programming, (ed. J. Minker) Morgan Kaufmann, 89–148.Google Scholar
  2. [Benferhat et al, 1992]
    S. Benferhat, D. Dubois, H. Prade, Representing default rules in possibilistic logic. KR'92, 673–684.Google Scholar
  3. [Bidoit and Froidevaux, 1987]
    Minimal subsumes default logic and circumscription in stratified logic programming, In LICS, New-York, 89–97.Google Scholar
  4. [Dubois et al.,1989]
    D.Dubois,J.Lang, H.Prade. Automated reasoning using possibilistic logic: semantics, belief revision, and variable certainty weights. UIA'89, 81–87.Google Scholar
  5. [Dubois et al., 1991]
    D. Dubois, J. Lang, H. Prade. Towards possibilistic logic programming. ICLP'91, 581–595.Google Scholar
  6. [Dubois et al., 1993]
    D. Dubois, J. Lang, H. Prade. “Possibilistic logic”. To appear in Handbook of Logic for Artificial Intelligence (D.M. Gabbay, ed.), vol. 3, 439–513.Google Scholar
  7. [Gärdenfors and Makinson, 1992]
    Non-monotonic inference based on expectations. Artificial Intelligence, to appear.Google Scholar
  8. [Goldszmidt and Pearl 1991]
    System-Z+: a formalism for reasoning with variable-strength defaults. AAAI-91, 399–404.Google Scholar
  9. [Kraus et al., 1990]
    S. Kraus, D. Lehmann, M. Magidor. Non-monotonic reasoning, preferential models and cumulative logics. Artificial Intelligence, 44: 167–207.Google Scholar
  10. [Lifischitz, 1985]
    Computing Circumscription, IJCAI'85, Los-Angeles.Google Scholar
  11. [Lloyd, 1984]
    Foundations of Logic Programming. Springer-Verlag 1984.Google Scholar
  12. [McCarthy, 1980]
    Circumscription — A form of non-monotonic reasoning. Artificial Intelligence, 13:27–39.Google Scholar
  13. [McCarthy, 1986]
    Application of circumscription to formalize commonsense reasoning. Artificial Intelligence, 28:89–116.Google Scholar
  14. [Pearl, 1990]
    System Z: A natural ordering of defaults with tractable applications to default reasoning. TARK'90, 121–135.Google Scholar
  15. [Przymusinski, 1988]
    On the relationship between Logic programming and Non-monotonic Reasoning. AAAI'88, 444–448.Google Scholar
  16. [Shoham, 1988]
    Reasoning About Change — Time and Causation from the Standpoint of Artificial Intelligence. Cambridge, Mass.: The MIT Press.Google Scholar
  17. [Subrahmanian, 1989]
    Mechanical proof procedures for many-valued lattice-based logic programming. Research report, Computer Science Dept., Syracuse Univ., N. Y., USA.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Salem Benferhat
    • 1
  • Didier Dubois
    • 1
  • Henri Prade
    • 1
  1. 1.I.R.I.T. (Univ. P. Sabatier)Toulouse 31062 CédexFrance

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