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Any-Time Knowledge Revision and Inconsistency Handling

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Formalisms for Reuse and Systems Integration (FMI 2014)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 346))

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Abstract

We propose and experiment a practical multi-level approach to maintain contradiction-free knowledge when some incoming additional information that can contradict the preexisting knowledge must be taken into account. The approach implements an any-time strategy that triggers successive reasoning paradigms ranging from credulous to computationally more intensive forms of skepticism about conflicting information. It makes use of recent dramatic computational progress in constraint satisfaction techniques for finite domains and Boolean-related search and reasoning. Interestingly, the structure of the approach and the involved techniques also apply for the more general issue of handling contradictory knowledge.

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References

  1. Béziau, J.-Y., Carnielli, W., Gabbay, D.M.: Handbook of Paraconsistency. Studies in Logic. College Publications (2007)

    Google Scholar 

  2. Ginsberg, M.L.: Readings in nonmonotonic reasoning. M. Kaufmann Publishers (1987)

    Google Scholar 

  3. Fermé, E.L., Hansson, S.O.: AGM 25 years - twenty-five years of research in belief change. J. Philosophical Logic 40(2), 295–331 (2011)

    Article  MATH  Google Scholar 

  4. Grégoire, É., Konieczny, S.: Logic-based approaches to information fusion. Information Fusion 7(1), 4–18 (2006)

    Article  Google Scholar 

  5. Zhang, D., Grégoire, É.: The landscape of inconsistency: a perspective. Int. J. Semantic Computing 5(3), 235–256 (2011)

    Google Scholar 

  6. Rossi, F., Beek, P.v., Walsh, T.: Handbook of Constraint Programming. Elsevier (2006)

    Google Scholar 

  7. Lecoutre, C.: Constraint Networks: Techniques and Algorithms. Wiley (2009)

    Google Scholar 

  8. Papadimitriou, C.H.: Computational Complexity. Addison-Wesley (1993)

    Google Scholar 

  9. Marques-Silva, J., Janota, M.: On the query complexity of selecting few minimal sets. Electronic Colloquium on Computational Complexity (ECCC) 21, 31 (2014)

    Google Scholar 

  10. Papadimitriou, C.H., Yannakakis, M.: Optimization, approximation, and complexity classes. Journal of Computer and System Sciences 43(3), 425 (1991)

    Article  MATH  MathSciNet  Google Scholar 

  11. Papadimitriou, C.H., Wolfe, D.: The complexity of facets resolved. Journal of Computer and System Sciences 37(1), 2–13 (1988)

    Article  MATH  MathSciNet  Google Scholar 

  12. Eiter, T., Gottlob, G.: On the complexity of propositional knowledge base revision, updates, and counterfactuals. Artificial Intelligence 57(2-3), 227–270 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  13. Belov, A., Marques-Silva, J.: Accelerating MUS extraction with recursive model rotation. In: Proceedings of the International Conference on Formal Methods in Computer-Aided Design (FMCAD 2011), pp. 37–40 (2011)

    Google Scholar 

  14. Marques-Silva, J., Heras, F., Janota, M., Previti, A., Belov, A.: On computing minimal correction subsets. In: Proceedings of the 23rd International Joint Conference on Artificial Intelligence, IJCAI 2013 (2013)

    Google Scholar 

  15. Liffiton, M.H., Malik, A.: Enumerating infeasibility: Finding multiple mUSes quickly. In: Gomes, C., Sellmann, M. (eds.) CPAIOR 2013. LNCS, vol. 7874, pp. 160–175. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  16. Lagniez, J.-M., Biere, A.: Factoring out assumptions to speed up MUS extraction. In: Järvisalo, M., Van Gelder, A. (eds.) SAT 2013. LNCS, vol. 7962, pp. 276–292. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  17. Grégoire, É., Lagniez, J.-M., Mazure, B.: An experimentally efficient method for (MSS,CoMSS) partitioning. In: Proceedings of the 28th Conference on Artificial Intelligence (AAAI 2014), pp. 2666–2673 (2014)

    Google Scholar 

  18. Eén, N., Sörensson, N.: An extensible SAT-solver. In: Giunchiglia, E., Tacchella, A. (eds.) SAT 2003. LNCS, vol. 2919, pp. 502–518. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  19. Reiter, R.: A logic for default reasoning. Artificial Intelligence 13(1-2), 81–132 (1980)

    Article  MATH  MathSciNet  Google Scholar 

  20. Grégoire, É., Mazure, B., Piette, C.: Boosting a complete technique to find MSS and MUS thanks to a local search oracle. In: International Joint Conference on Artificial Intelligence (IJCAI 2007), pp. 2300–2305 (2007)

    Google Scholar 

  21. Hamscher, W., Console, L., de Kleer, J.: Readings in Model-Based Diagnosis. Morgan Kaufmann (1992)

    Google Scholar 

  22. Feldman, A., Kalech, M., Provan, G.: Proceedings of the 24th International Workshop on Principles of Diagnosis (DX-2013) (Electronic proceedings) (2013), http://www.dx-2013.org/proceedings.php

  23. Kautz, H.A., Selman, B.: Pushing the envelope: Planning, propositional logic and stochastic search. In: Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference (AAAI 1996), vol. 2, pp. 1194–1201 (1996)

    Google Scholar 

  24. Belov, J.A., Marques-Silva: MUSer2: An efficient MUS extractor, system description. Journal on Satisfiability, Boolean Modeling and Computation (2012)

    Google Scholar 

  25. Doyle, J.: A truth maintenance system. Artificial Intelligence 12(3), 231–272 (1979)

    Article  MathSciNet  Google Scholar 

  26. de Kleer, J.: An assumption-based TMS. Artificial Intelligence 28(2), 127–162 (1986)

    Article  Google Scholar 

  27. Grégoire, É., Lagniez, J.-M., Mazure, B.: Questioning the importance of WCORE-like minimization steps in MUC-finding algorithms. In: Proceedings of the IEEE 25th International Conference on Tools with Artificial Intelligence (ICTAI 2013), pp. 923–930 (2013)

    Google Scholar 

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Correspondence to Éric Grégoire .

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Grégoire, É. (2015). Any-Time Knowledge Revision and Inconsistency Handling. In: Bouabana-Tebibel, T., Rubin, S. (eds) Formalisms for Reuse and Systems Integration. FMI 2014. Advances in Intelligent Systems and Computing, vol 346. Springer, Cham. https://doi.org/10.1007/978-3-319-16577-6_12

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  • DOI: https://doi.org/10.1007/978-3-319-16577-6_12

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16576-9

  • Online ISBN: 978-3-319-16577-6

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