Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
B. El. Ayeb, P. Marquis, and M. Rusinowitch. Deductive/Abductive Diagnosis: The DA-Principles. In Proceeding of ECAI, Stokholm, Sweden, 1990.
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.
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.
C. L. Chang and R. C. Lee. Symbolic Logic and Mechanical Theorem Proving. Academic Press, New York, 1973.
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.
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.
P.T. Cox and T. Pietrzykowski. General diagnosis by abductive inference. In Symposium on Logic Programming, pages 183–189, 1987.
R. Davis. Diagnostic reasoning based on structure and behaviour. Artificial Intelligence, 24:347–410, 1984.
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.
J. De-Kleer. Diagnosing multiple faults. Artificial Intelligence, 32:97–130, 1987.
J. De-Kleer and B.C. Williams. Diagnosis with behavioural modes. In Proceedings of IJCAI, Detroit.MI(USA). 1989.
N. Dershowitz. Termination of rewriting. Journal of Symbolic Computation, 3(1 & 2):69–116, 1987.
R. Kowalski. Studies in the completeness and efficiency of theorem-proving by resolution. PhD thesis, University of Edinburgh, 1970.
P. Marquis. A Note on Prime Implicants. Technical Report 90-R-089. CRIN. 1990.
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.
R. Milne. On-line artificial intelligence. In Journées Systèmes Experts, pages 437–451, Avignon (France), 1987.
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.
D. Poole. Normality and faults in logic-based diagnosis. In Proceedings of IJCAI. pages 1304–1310. Detroit,MI(USA), 1989.
D. Poole. Representing knowledge for logic-based diagnosis. In ICOT. editor, International Conference on Fifth Generation Computer Systems, pages 1282–1290, 1988.
W.V. Quine. On cores and prime implicants of truth functions. American Math. Monthly, 66:755–760, 1959.
O. Raiman. Diagnosis as a trial: the alibi principle. In IBM Workshop on Model-Based Diagnosis, pages 1–10, Paris (France), July 1989.
J. A. Reggia, D. S. Nau, and P. Y. Wang. A formal model of diagnostic inference. Information Sciences, 37:227–285, 1985.
R. Reiter. A theory of diagnosis from first principles. Artificial Intelligence, 32:57–95, 1987.
M. Rusinowitch. Démonstration automatique-Techniques de réécriture. InterEditions. 1989.
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.
R. Socher-Ambrosius. Using Theory Resolution to Simplify Interpreted Formulae. SEKIREPORT SR-88-16. Universität Kaiserslautern. 1988.
M. Stickel. Automated deduction by theory resolution. Journal of Automated Reasoning, 1(4):333–356, 1985.
P. Struss. Diagnosis as a process. In IBM Workshop on Model-Based Diagnosis. Paris (France), July 1989.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1990 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
El. Ayeb, B., Marquis, P., Rusinowitch, M. (1990). A new diagnosis approach by deduction and abduction. In: Gottlob, G., Nejdl, W. (eds) Expert Systems in Engineering Principles and Applications. ESE 1990. Lecture Notes in Computer Science, vol 462. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-53104-1_29
Download citation
DOI: https://doi.org/10.1007/3-540-53104-1_29
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-53104-3
Online ISBN: 978-3-540-46711-3
eBook Packages: Springer Book Archive