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An Algorithmic Approach to Recover Inconsistent Knowledge-Bases

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Logics in Artificial Intelligence (JELIA 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1919))

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Abstract

We consider an algorithmic approach for revising inconsistent data and restoring its consistency. This approach detects the “spoiled” part of the data (i.e., the set of assertions that cause inconsistency), deletes it from the knowledge-base, and then draws classical conclusions from the “recovered” information. The essence of this approach is its coherence with the original (possibly inconsistent) data: On one hand it is possible to draw classical conclusions from any data that is not related to the contradictory information, while on the other hand, the only inferences allowed by this approach are those that do not contradict any former conclusion. This method may therefore be used by systems that restore consistent information and are obliged to their resource of information. Common examples of this case are diagnostic procedures that analyse faulty components of malfunction devices, and database management systems that amalgamate distributed knowledgebases.

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References

  1. O. Arieli, A. Avron. Four-valued diagnoses for stratified knowledge-bases. Proc. CSL’96, Selected Papers (D. Van-Dalen, M. Bezem, editors), Springer Verlag, LNCS No.1258, pages 1–17, 1997.

    Google Scholar 

  2. O. Arieli, A. Avron. A model theoretic approach to recover consistent data from inconsistent knowledge-bases. Journal of Automated Reasoning 22(3), pages 263–309, 1999.

    Article  MATH  MathSciNet  Google Scholar 

  3. N.D. Belnap. A useful four-valued logic. Modern Uses of Multiple-Valued Logic (G. Epstein, J.M. Dunn, editors), Reidel Publishing Company, pages 7–37, 1977.

    Google Scholar 

  4. N.D. Belnap. How computer should think. Contemporary Aspects of Philosophy (G. Ryle, editor), Oriel Press, pages 30–56, 1977.

    Google Scholar 

  5. S. Benferhat, D. Dubois, H. Prade. How to infer from inconsistent beliefs without revising? Proc. IJCAI’95, pages 1449–1455, 1995.

    Google Scholar 

  6. D. Dubois, J. Lang, H. Prade. Possibilistic logic. Handbook of Logic in Artificial Intelligence and Logic Programming (D. Gabbay, C. Hogger, J. Robinson, editors), Oxford Science Publications, pages 439–513, 1994.

    Google Scholar 

  7. M. Fitting. Kleene’s three-valued logics and their children. Fundamenta Informaticae 20, pages 113–131, 1994.

    Google Scholar 

  8. M. Gelfond, V. Lifschitz. The stable model semantics for logic programming. Proc. of the 5th Logic Programming Symp. (R. Kowalski, K. Browen, editors) MIT Press,Cambridge, MA, pages 1070–1080, 1988.

    Google Scholar 

  9. M. Ginsberg. Counterfactuals. Artificial Intelligence 30(1), pages 35–79, 1986.

    Article  MATH  MathSciNet  Google Scholar 

  10. S. Kraus, D. Lehmann, M. Magidor. Nonmonotonic reasoning, preferential models and cumulative logics. Artificial Intelligence 44(1-2), pages 167–207, 1990.

    Article  MATH  MathSciNet  Google Scholar 

  11. D. Makinson. General patterns in nonmonotonic reasoning. Handbook of Logic in Artificial Intelligence and Logic Programming 3 (D. Gabbay, C. Hogger, J. Robinson, editors), Oxford Science Publishers, pages 35–110, 1994.

    Google Scholar 

  12. J. Pearl. Reasoning under uncertainty. Annual Review of Computer Science 4, pages 37–72, 1989.

    Article  MathSciNet  Google Scholar 

  13. G. Priest. Minimally Inconsistent LP. Studia Logica 50, pages 321–331, 1991.

    Article  MATH  MathSciNet  Google Scholar 

  14. V.S. Subrahmanian. Mechanical proof procedures for many valued lattice-based logic programming. Journal of Non-Classical Logic 7, pages 7–41, 1990.

    MathSciNet  Google Scholar 

  15. G. Wagner. Vivid logic. Springer-Verlag, LNAI No.764, 1994.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science, K.U.Leuven Celestijnenlaan 200A, B-3001, Heverlee, Belgium

    Ofer Arieli

Authors
  1. Ofer Arieli
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Editor information

Editors and Affiliations

  1. Department of Applied Mathematics, E.T.S.I. Informática, University of Málaga, 29071, Málaga, Spain

    Manuel Ojeda-Aciego  & Inma P. de Guzmán  & 

  2. Intelligent Systems Department, Computer Science Institute, University of Leipzig, Augustusplatz 10-11, 04109, Leipzig, Germany

    Gerhard Brewka

  3. Center for Artificial Intelligence, Department of Computer Science, University of Lisbon, 2825-114, Caparica, Portugal

    Luís Moniz Pereira

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© 2000 Springer-Verlag Berlin Heidelberg

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Arieli, O. (2000). An Algorithmic Approach to Recover Inconsistent Knowledge-Bases. In: Ojeda-Aciego, M., de Guzmán, I.P., Brewka, G., Moniz Pereira, L. (eds) Logics in Artificial Intelligence. JELIA 2000. Lecture Notes in Computer Science(), vol 1919. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-40006-0_11

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  • DOI: https://doi.org/10.1007/3-540-40006-0_11

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41131-4

  • Online ISBN: 978-3-540-40006-6

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