Temporal Logic pp 301-316 | Cite as

The Abductive Event Calculus as a general framework for temporal databases

  • Kristof Van Belleghem
  • Marc Denecker
  • Danny De Schreye
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 827)


In earlier work, we have shown that the formalism of abductive logic programs with FOL integrity constraints provides, under a completion semantics, the same declarative expressivity for representing incomplete information as full first order logic. We have shown how the combination of this formalism with a variant of the Event Calculus of Kowalski and Sergot results in a correct and very expressive framework for temporal reasoning and representation. In this paper we demonstrate how this Abductive Event Calculus formalism provides a general frame-work for the representation and use of temporal databases. On the declarative level, it is particularly convenient for the representation of incomplete knowledge. Complementary, on the procedural level, we are able to provide a number of simple algorithms using abduction and deduction to test the consistency of the base, answer queries, update the database, handle complex formulas and resolve inconsistency. Furthermore, the use of the database for general temporal problem solving is possible using the known Event Calculus and Logic Programming methods. In particular we show how planning is possible in this kind of temporal database.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    J. F. Allen. Maintaining Knowledge About Temporal Intervals. CACM, 26(11):832–843, 1983.Google Scholar
  2. 2.
    J. F. Allen. Towards a General Theory of Action and Time. Artifical Intelligence, 23(11):123, 1984.Google Scholar
  3. 3.
    K. Clark. Negation as failure. In H. Gallaire and J. Minker, editors, Logic and databases, pages 293–322. Plenum Press, 1978.Google Scholar
  4. 4.
    L. Console, D. Theseider Dupre, and P. Torasso. On the relationship between abduction and deduction. Journal of Logic and Computation, 1(5):661–690, 1991.Google Scholar
  5. 5.
    M. Denecker. Knowledge Representation and Reasoning in Incomplete Logic Programming. PhD thesis, Department of Computer Science, K.U.Leuven, 1993.Google Scholar
  6. 6.
    M. Denecker and D. De Schreye. SLDNFA; an abductive procedure for normal abductive programs. In K. Apt, editor, Proceedings of the International Joint Conference and Symposium on Logic Programming, Washington, 1992.Google Scholar
  7. 7.
    M. Denecker, L. Missiaen, and M. Bruynooghe. Temporal reasoning with abductive event calculus. In Proceedings of ECAI 92, Vienna, 1992.Google Scholar
  8. 8.
    K. Eshghi. Abductive planning with event calculus. In R. Kowalski and K. Bowen, editors, Proceedings of the 5th ICLP, 1988.Google Scholar
  9. 9.
    C. Evans. The Macro-Event Calculus: Representing Temporal Granularity. In Proceedings of PRICAI, Tokyo, 1990.Google Scholar
  10. 10.
    M. Gelfond and V. Lifschitz. Describing Action and Change by Logic Programs. In Proc. of the 9th Int. Joint Conf. and Symp. on Logic Programming, 1992.Google Scholar
  11. 11.
    A. Kakas and P. Mancarella. Constructive abduction in logic programming. Technical report, Dipartimento di Informatica, University of Pisa, 1993.Google Scholar
  12. 12.
    R. A. Kowalski. Logic for problem solving. Elsevier Science Publisher, 1976.Google Scholar
  13. 13.
    R. A. Kowalski. Database updates in the event calculus. Journal of Logic Programming, 1992, 1992.Google Scholar
  14. 14.
    R. A. Kowalski and M. Sergot. A logic-based calculus of events. New Generation Computing, 4(4):319–340, 1986.Google Scholar
  15. 15.
    J. Lloyd. Foundations of Logic Programming. Springer-Verlag, 1987.Google Scholar
  16. 16.
    J. Lloyd and R. Topor. Making prolog more expressive. Journal of logic programming, 1(3):225–240, 1984.Google Scholar
  17. 17.
    L. Missiaen. Localized abductive planning with the event calculus. PhD thesis, Department of Computer Science, K.U.Leuven, 1991.Google Scholar
  18. 18.
    A. Porto and C. Ribeiro. Temporal inference with a point-based interval algebra. In Proceedings of ECAI 92, Vienna, pages 374–378, 1992.Google Scholar
  19. 19.
    M. Shanahan. Prediction is deduction but explanation is abduction. In Proceedings of IJCAI 89, page 1055, 1989.Google Scholar
  20. 20.
    M. Shanahan. Representing continuous change in the event calculus. In Proceedings of the 9th ECAI, page 598, 1990.Google Scholar
  21. 21.
    S. Sripada. A metalogical programming approach to reasoning about time in knowledge bases. In Proceedings of IJCAI 93, 1993.Google Scholar
  22. 22.
    A. Weigel and R. Bleisinger. Support for resolving Contradictions in Time Interval Networks. In Proceedings of ECAI 92, Vienna, pages 379–383, 1992.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • Kristof Van Belleghem
    • 1
  • Marc Denecker
    • 1
  • Danny De Schreye
    • 1
  1. 1.Department of Computer ScienceK.U.LeuvenHeverleeBelgium

Personalised recommendations