Dealing Automatically with Exceptions by Introducing Specificity in ASP

  • Laurent Garcia
  • Stéphane Ngoma
  • Pascal Nicolas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5590)


Answer Set Programming (ASP), via normal logic programs, is known as a suitable framework for default reasoning since it offers both a valid formal model and operational systems. However, in front of a real world knowledge representation problem, it is not easy to represent information in this framework. That is why the present article proposed to deal with this issue by generating in an automatic way the suitable normal logic program from a compact representation of the information. This is done by using a method, based on specificity, that has been developed for default logic and which is adapted here to ASP both in theoretical and practical points of view.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bidoit, N., Froidevaux, C.: General logical databases and programs: Default logic semantics and stratification. Information and Computation 91(1), 15–54 (1991)CrossRefMATHGoogle Scholar
  2. 2.
    Borges Garcia, B., Pereira Lopes, J.G., Varejão, F.: Compiling default theory int extended logic programming. In: Monard, M.C., Sichman, J.S. (eds.) SBIA 2000 and IBERAMIA 2000. LNCS, vol. 1952, pp. 207–216. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  3. 3.
    De Bruijn, J., Heymans, S., Pearce, D., Polleres, A., Ruckhaus, E. (eds.): Proc. of ICLP 2008 Workshop on Applications of Logic Programming to the (Semantic) Web and Web Services, ALPSWS 2008 (2008)Google Scholar
  4. 4.
    Bruni, R.: On Exact Selection of Minimally Unsatisfiable Subformulae. Ann. Math. Artif. Intell. 43(1-4), 35–50 (2005)CrossRefMATHGoogle Scholar
  5. 5.
    Delgrande, J.P., Schaub, T.: Compiling specificity into approaches to nonmonotonic reasoning. Artif. Intell. 90(1-2), 301–348 (1997)CrossRefMATHGoogle Scholar
  6. 6.
    Dupin de Saint-Cyr, F., Prade, H.: Handling uncertainty and defeasibility in a possibilistic logic setting. Int. J. Approx. Reasoning 49(1), 67–82 (2008)CrossRefMATHGoogle Scholar
  7. 7.
    Eiter, T., Gottlob, G.: On the Complexity of Propositional Knowledge Base Revision, Updates and Counterfactuals. Artif. Intell. 57(2-3), 227–270 (1992)CrossRefMATHGoogle Scholar
  8. 8.
    Garcia de la Banda, M., Pontelli, E. (eds.): ICLP 2008. LNCS, vol. 5366. Springer, Heidelberg (2008)MATHGoogle Scholar
  9. 9.
    Gebser, M., Kaufmann, B., Neumann, A., Schaub, T.: Conflict-driven answer set solving. In: Proc. of IJCAI 2007, pp. 386–392 (2007)Google Scholar
  10. 10.
    Gelfond, M., Lifschitz, V.: The stable model semantics for logic programming. In: Proc. of ICLP 1988, pp. 1070–1080. MIT Press, Cambridge (1988)Google Scholar
  11. 11.
    Gelfond, M., Lifschitz, V.: Classical negation in logic programs and disjunctive databases. New Generation Computing 9(3-4), 363–385 (1991)CrossRefMATHGoogle Scholar
  12. 12.
    Grégoire, É., Mazure, B., Piette, C.: Boosting a Complete Technique to Find MSS and MUS thanks to a Local Search Oracle. In: Proc. of IJCAI 2007, pp. 2300–2305 (2007)Google Scholar
  13. 13.
    Inoue, K., Kudoh, Y.: Learning extended logic programs. In: Proc. of IJCAI 1997, pp. 176–181 (1997)Google Scholar
  14. 14.
    Kraus, S., Lehmann, D.J., Magidor, M.: Nonmonotonic reasoning, preferential models and cumulative logics. Artif. Intell. 44(1-2), 167–207 (1990)CrossRefMATHGoogle Scholar
  15. 15.
    Leone, N., Pfeifer, G., Faber, W., Eiter, T., Gottlob, G., Perri, S., Scarcello, F.: The dlv system for knowledge representation and reasoning. ACM Transactions on Computational Logic 7(3), 499–562 (2006)CrossRefGoogle Scholar
  16. 16.
    Liffiton, M.H., Sakallah, K.A.: Algorithms for Computing Minimal Unsatisfiable Subsets of Constraints. J. Autom. Reasoning 40(1), 1–33 (2008)CrossRefMATHGoogle Scholar
  17. 17.
    Nicolas, P., Garcia, L., Stéphan, I., Lefèvre, C.: Possibilistic uncertainty handling for answer set programming. Ann. Math. Artif. Intell. 47(1-2), 139–181 (2006)CrossRefMATHGoogle Scholar
  18. 18.
    Papadimitriou, C.H., Wolfe, D.: The Complexity of Facets Resolved. J. Computer and System Sciences 37(1), 2–13 (1988)CrossRefMATHGoogle Scholar
  19. 19.
    Pearl, J.: System Z: A natural ordering of defaults with tractable applications to nonmonotonic reasoning. In: Proc. of Theoritical Aspects of Reasoning about Knowledge (TARK 1990), pp. 121–135 (1990)Google Scholar
  20. 20.
    Reiter, R.: A logic for default reasoning. Artif. Intell. 13, 81–132 (1980)CrossRefMATHGoogle Scholar
  21. 21.
    Simons, P., Niemelä, I., Soininen, T.: Extending and implementing the stable model semantics. Artif. Intell. 138(1-2), 181–234 (2002)CrossRefMATHGoogle Scholar
  22. 22.
    You, J.H., Wang, X., Yuan, L.Y.: Compiling defeasible inheritance networks to general logic programs. Artif. Intell. 113(1-2), 247–268 (1999)CrossRefMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Laurent Garcia
    • 1
  • Stéphane Ngoma
    • 1
  • Pascal Nicolas
    • 1
  1. 1.LERIA, UFR SciencesUniversity of AngersANGERS cedex 01France

Personalised recommendations