A new diagnosis approach by deduction and abduction

  • Béchir El. Ayeb
  • Pierre Marquis
  • Michaël Rusinowitch
Model-Based Diagnosis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 462)


Much research has been devoted to diagnosis, where two main approaches have been pointed out: the empirical-based diagnostic approach and the model-based diagnostic one. These two approaches can be characterized by the kind of knowledge that has to be specified and the diagnosis method that has to be used. However, it seems particularly difficult in real-world applications to obtain a complete description of the faulty (dually, correct) behaviour of a system.

Our contribution is a diagnostic procedure based on both deduction and abduction, which is sufficiently flexible to deal with several presentations of the knowledge. Both deductive and abductive steps rely on the same first-order theorem proving strategy.


Inference Rule Predicate Symbol Intended Interpretation Abductive Inference Prime Implicants 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    B. El. Ayeb, P. Marquis, and M. Rusinowitch. Deductive/Abductive Diagnosis: The DA-Principles. In Proceeding of ECAI, Stokholm, Sweden, 1990.Google Scholar
  2. [2]
    B.El. Ayeb. When Developing KBS for Real-Wold Applications. In 10th International Conference on Second Generation of Expert Systems, May/June, Avignon (France). 1990.Google Scholar
  3. [3]
    B.El. Ayeb and J.P. Finance. On Cooperation between deep and shallow reasoning, pages 95–118. Volume Diagnosis and Learning, Elsevier Science Publishing Cie, 1988.Google Scholar
  4. [4]
    C. L. Chang and R. C. Lee. Symbolic Logic and Mechanical Theorem Proving. Academic Press, New York, 1973.Google Scholar
  5. [5]
    L. Console, D. T. Dupré, and P. Torasso. A theory of diagnosis for incomplete causal models. In Proceedings of IJCAI, pages 1311–1317, Detroit,MI(USA), 1989.Google Scholar
  6. [6]
    P.T. Cox and T. Pietrzykowski. Causes for events: their computation and applications. In 8th Conference on Automated Deduction, pages 608–621, LNCS 230, Springer-Verlag, 1986.Google Scholar
  7. [7]
    P.T. Cox and T. Pietrzykowski. General diagnosis by abductive inference. In Symposium on Logic Programming, pages 183–189, 1987.Google Scholar
  8. [8]
    R. Davis. Diagnostic reasoning based on structure and behaviour. Artificial Intelligence, 24:347–410, 1984.Google Scholar
  9. [9]
    R. Davis and W. Hamsher. Model-based Reasoning: Troubleshooting, chapter 8, pages 297–346. Volume Explorating AI: Survey Talks from Nat. Conf. on AI, Morgan Kaufmann, San Mateo, CA(USA). 1988.Google Scholar
  10. [10]
    J. De-Kleer. Diagnosing multiple faults. Artificial Intelligence, 32:97–130, 1987.Google Scholar
  11. [11]
    J. De-Kleer and B.C. Williams. Diagnosis with behavioural modes. In Proceedings of IJCAI, Detroit.MI(USA). 1989.Google Scholar
  12. [12]
    N. Dershowitz. Termination of rewriting. Journal of Symbolic Computation, 3(1 & 2):69–116, 1987.Google Scholar
  13. [13]
    R. Kowalski. Studies in the completeness and efficiency of theorem-proving by resolution. PhD thesis, University of Edinburgh, 1970.Google Scholar
  14. [14]
    P. Marquis. A Note on Prime Implicants. Technical Report 90-R-089. CRIN. 1990.Google Scholar
  15. [15]
    P. Marquis. Une étude formelle de la recherche d'explications fondée sur la logique. In Actes des Journées Françaises de l'Apprentissage, pages 137–151, 1989.Google Scholar
  16. [16]
    R. Milne. On-line artificial intelligence. In Journées Systèmes Experts, pages 437–451, Avignon (France), 1987.Google Scholar
  17. [17]
    D.S. Nau and J.A. Reggia. Relationships between deductive and abductive inference in knowledge-based diagnostic problem solving. In Kershberg, editor. First International Workshop on Expert Database Systems, pages 549–558, Benjamin Cummings Publishing Company, 1986.Google Scholar
  18. [18]
    D. Poole. Normality and faults in logic-based diagnosis. In Proceedings of IJCAI. pages 1304–1310. Detroit,MI(USA), 1989.Google Scholar
  19. [19]
    D. Poole. Representing knowledge for logic-based diagnosis. In ICOT. editor, International Conference on Fifth Generation Computer Systems, pages 1282–1290, 1988.Google Scholar
  20. [20]
    W.V. Quine. On cores and prime implicants of truth functions. American Math. Monthly, 66:755–760, 1959.Google Scholar
  21. [21]
    O. Raiman. Diagnosis as a trial: the alibi principle. In IBM Workshop on Model-Based Diagnosis, pages 1–10, Paris (France), July 1989.Google Scholar
  22. [22]
    J. A. Reggia, D. S. Nau, and P. Y. Wang. A formal model of diagnostic inference. Information Sciences, 37:227–285, 1985.Google Scholar
  23. [23]
    R. Reiter. A theory of diagnosis from first principles. Artificial Intelligence, 32:57–95, 1987.Google Scholar
  24. [24]
    M. Rusinowitch. Démonstration automatique-Techniques de réécriture. InterEditions. 1989.Google Scholar
  25. [25]
    M. Rusinowitch. Theorem-proving with resolution and superposition: an extension of Knuth and Bendix procedure to a complete set of inference rules. In Proceedings of the International Conference on Fifth Generation Computer Systems, 1988.Google Scholar
  26. [26]
    R. Socher-Ambrosius. Using Theory Resolution to Simplify Interpreted Formulae. SEKIREPORT SR-88-16. Universität Kaiserslautern. 1988.Google Scholar
  27. [27]
    M. Stickel. Automated deduction by theory resolution. Journal of Automated Reasoning, 1(4):333–356, 1985.Google Scholar
  28. [28]
    P. Struss. Diagnosis as a process. In IBM Workshop on Model-Based Diagnosis. Paris (France), July 1989.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1990

Authors and Affiliations

  • Béchir El. Ayeb
    • 1
  • Pierre Marquis
    • 1
  • Michaël Rusinowitch
    • 1
  1. 1.CRIN/INRIAVandoeuvre-lès-Nancy CedexFrance

Personalised recommendations