Strong Conditional Logic

  • Cláudia Nalon
  • Jacques Wainer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1515)


This paper presents the semantic of SCL, a strong conditional logic that has the desirable properties of standard conditional logics but also deals with modes of reasoning that are hard for these logics like inheritance and irrelevance. The approach taken here produces fewer models (and then best results), even when considering strenghted conditional logics.


Knowledge Base Normal World Strict Rule Propositional Formula Default Theory 
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.
    Boutilier, C.: Conditional Logics of Normality: A Modal Approach. Artificial Intelligence 68, 87–154 (1994)zbMATHCrossRefMathSciNetGoogle Scholar
  2. 2.
    Brewka, G.: Cumulative Default Logic: In Defense of Nonmonotonic Inference Rules. Artificial Intelligence 50(2), 183–205 (1991)zbMATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Delgrande, J.P.: A First-Order Conditional Logical for Prototypical Properties. Artificial Intelligence 33(1), 105–130 (1987)zbMATHCrossRefMathSciNetGoogle Scholar
  4. 4.
    Delgrande, J.P.: An Approach to Default Reasoning Based on a First-Order Conditional Logic: Revised Report. Artificial Intelligence 36(1), 63–90 (1988)zbMATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Delgrande, J.P.: A preference Approach to Default Reasoning: Preliminary Report. In: American Association for Artificial Intelligence Conference, Seattle, WA (July 1994)Google Scholar
  6. 6.
    Freund, M., Lehmann, D., Morris, P.: Rationality, Transitivity and Contraposition. Artificial Intelligence 52, 191–203 (1991)zbMATHCrossRefMathSciNetGoogle Scholar
  7. 7.
    Geffner, H., Pearl, J.: Conditional Entailment: Bridging Two Approaches To Default Reasoning. Artificial Intelligence 53, 209–244 (1991)CrossRefMathSciNetGoogle Scholar
  8. 8.
    Kraus, S., Lehmann, D., Magidor, M.: Nonmonotonic Reasoning, Preferential Models and Cumulative Logics. Artificial Intelligence 44, 167–207 (1990)zbMATHCrossRefMathSciNetGoogle Scholar
  9. 9.
    Lehmann, D., Magidor, M.: What Does a Conditional Knowledge Base Entail? Artificial Intelligence 55(1), 1–60 (1992)zbMATHCrossRefMathSciNetGoogle Scholar
  10. 10.
    Marek, W., Truszczynski, M.: Autoepistemic Logic. Journal of the ACM 38, 588–619 (1991)zbMATHCrossRefMathSciNetGoogle Scholar
  11. 11.
    McCarthy, J.: Circumscription - A Form Of Nonmonotonic Reasoning. Artificial Intelligence 13, 27–39 (1980)zbMATHCrossRefMathSciNetGoogle Scholar
  12. 12.
    Moore, R.C.: Semantical Considerations on Nonmonotonic Logic. Artificial Intelligence 25(1), 75–94 (1985)zbMATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    Nalon, C.: Lógica Condicional Forte. (Dissertação de Mestrado), Universidade Estadual de Campinas, São Paulo (1997)Google Scholar
  14. 14.
    Pearl, J.: System Z: A natural ordering of defaults with tractable applications to nonmonotonic reasoning. In: Proceedings of the Third Conference on Theoretical Aspects of Reasoning About Knowledge, Pacific Grove, Ca., pp. 121–135 (1990)Google Scholar
  15. 15.
    Reiter, R.: A logic for default reasoning. Artificial Intelligence 13(1,2), 81–132 (1980)zbMATHCrossRefMathSciNetGoogle Scholar
  16. 16.
    Shoham, Y.: Reasoning About Change: Time and Causation from the Standpoint of Artificial Intelligence. MIT Press, Cambridge (1988)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Cláudia Nalon
    • 1
  • Jacques Wainer
    • 1
  1. 1.Institute of Computing StateUniversity of CampinasCampinasBrazil

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