Handling hard rules and default rules in possibilistic logic

  • Salem Benferhat
Possibility Theory
Part of the Lecture Notes in Computer Science book series (LNCS, volume 945)


This paper extends results done jointly with Dubois and Prade [3] about reasoning with generic knowledge in a possibilistic setting. We propose an approach to reasoning with both hard and default rules. We mean by a hard rule, the complete information “if we observe φ then we conclude (certainly) ψ”, and by a default rule, the generic information “if we observe φ then generally we conclude ψ”.


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  1. [1]
    E.W. Adams (1975). The Logic of Conditionals. Dordrecht: D. Reidel.Google Scholar
  2. [2]
    S. Benferhat (1994) Raisonnement non-monotone et traitement de l'inconsistance en logique possibiliste. Thèse de l'Université P. Sabatier, Toulouse.Google Scholar
  3. [3]
    S. Benferhat, D. Dubois, H. Prade (1992) Representing default rules in possibilistic logic. KR'92, 673–684.Google Scholar
  4. [4]
    S. Benferhat, C. Cayrol, D. Dubois, J. Lang, H. Prade (1993) Inconsistency management and prioritized syntax-based entailment. Proc. of IJCAI'93.Google Scholar
  5. [5]
    D. Dubois, J. Lang, H. Prade (1994). Possibilistic logic. To appear in Handbook of Logic for Artificial Intelligence (D.M. Gabbay, ed.), vol. 3, 439–513.Google Scholar
  6. [6]
    D.Dubois, H. Prade (1991) Possibilistic logic, preferential models, nonmonotonicity and related issues. IJCAI'91, 419–424.Google Scholar
  7. [7]
    D. Dubois, H. Prade.(1993) Conditional Objects as Non-monotonic Consequence Relationships. Technical report, IRIT-93-08-R (University of Toulouse).Google Scholar
  8. [8]
    L. Fariñas del Cerro, A. Herzig, and J. Lang (1992). From expectation-based nonmonotonic reasoning to conditional logics. Working Notes of the 4th Inter. Workshop on Nonmonotonic Reasoning, Plymouth, Vermont, May 28–31, 79–86.Google Scholar
  9. [9]
    M. Goldszmidt, et J. Pearl (1991). On the consistency of defeasible databases. Artificial Intelligence 52:121–149.Google Scholar
  10. [10]
    S. Kraus, D. Lehmann, and M. Magidor (1990). Nonmonotonic reasoning, preferential models and cumulative logics. Artificial Intelligence 44:167–207.Google Scholar
  11. [11]
    P. Lamarre (1992), A Promenade from Monotonicity to Non-Monotonicity Following a Theorem Prover. Proc. of KR'92.Google Scholar
  12. [12]
    D. Lehmann (1989), What does a conditional knowledge base entail? Proc. KR'89, pages 357–367.Google Scholar
  13. [13]
    J. Pearl (1988), Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann Publ. Inc., San Mateo, Ca., 1988.Google Scholar
  14. [14]
    J. Pearl (1990). System Z: a natural ordering of defaults with tractable applications to default reasoning. Proc.TARK, 121–135.Google Scholar
  15. [15]
    R. Reiter (1980), A Logic for Default Reasoning; Artificial Intelligence N∘13, 81–132.Google Scholar
  16. [16]
    Y. Shoham, (1988), Reasoning About Change — Time and Causation from the Standpoint of Artificial Intelligence. Cambridge, Mass.: The MIT Press.Google Scholar
  17. [17]
    R. R. Yager (1993), On the completion of priority orderings in nonmonotonic reasoning” Technical Report #1216, Iona College.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Salem Benferhat
    • 1
  1. 1.I.R.I.T. (U.P.S.)Toulouse 31062 CedexFrance

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