Skip to main content
SpringerLink
Log in

Study of symmetry in qualitative temporal interval networks

  • Conference paper
  • First Online:
Artificial Intelligence: Methodology, Systems, and Applications (AIMSA 1998)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1480))

Abstract

Symmetry has been studied in both propositional calculus and discrete constraint satisfaction problems. This has been shown to reduce considerably the search space. In this paper, we extend the study to qualitative interval networks. We provide experimental tests on the performances of a variant of Ladkin and Reinefeld's search algorithm in the following two cases: (1) the algorithm as provided by its authors, with no advantage of symmetry, and (2) the algorithm to which is added symmetry detection during the search. The experiments show that symmetries are profitable for hard problems.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. J F Allen. Maintaining knowledge about temporal intervals. Communications of the Association for Computing Machinery, 26(11):832–843, 1983.

    MATH  Google Scholar 

  2. B Benhamou. Study of symmetry in constraint satisfaction problems. In Proceedings PPCP, 1994.

    Google Scholar 

  3. B Benhamou and L Sais. Tractability through symmetries in propositional calculus. Automated Reasoning, 12:89–102, 1994.

    Article  MATH  MathSciNet  Google Scholar 

  4. S Benzer. On the topology of the genetic fine structure. Proceedings Nat. Acad. Sci., USA 45:1607–1620, 1959.

    Article  Google Scholar 

  5. E C Freuder. Synthesizing constraint expressions. Communications of the Association for Computing Machinery, 21:958–966, 1978.

    MATH  MathSciNet  Google Scholar 

  6. E C Freuder. A sufficient condition for backtrack-free search. Journal of the Association for Computing Machinery, 29:24–32, 1982.

    MATH  MathSciNet  Google Scholar 

  7. E C Freuder. Eliminating interchangeable values in constraint satisfaction problems. In Proceedings of the AAAI-91, pages 227–233, Anaheim, CA, 1991. AAAI Press/The MIT Press.

    Google Scholar 

  8. J Gasching. Experimental case studies of backtrack vs. waltz-type vs. new algorithms for satisfying assignment problems. In Proceedings of the Second Biennial Conference of the Canadian Society for Computational Studies of Intelligence, pages 268–277, Toronto, Ont., 1978.

    Google Scholar 

  9. M C Golumbic and R Shamir. Complexity and algorithms for reasoning about time: a graph-theoretic approach. Journal of the Association for Computing Machinery, 40(5):1108–1133, 1993.

    MATH  MathSciNet  Google Scholar 

  10. R M Haralick and G L Elliott. Increasing tree search efficiency for constraint satisfaction problems. Artificial Intelligence, 14:263–313, 1980.

    Article  Google Scholar 

  11. A Haselbök. Exploiting interchangeabilities in constraint satisfaction problems. In Proceedings of the IJCAI-93, pages 282–287, Chambéry, France, 1993.

    Google Scholar 

  12. A Isli and H Bennaceur. Qualitative interval networks: combining path consistency and circuit consistency in the search for a solution. In Proceedings of the International Workshop of Temporal Representation and Reasoning (TIME-96), Key West, Florida, 1996.

    Google Scholar 

  13. P Ladkin and A Reinefeld. Effective solution of qualitative constraint problems. Artificial Intelligence, 57:105–124, 1992.

    Article  MathSciNet  Google Scholar 

  14. A K Mackworth. Consistency in networks of relations. Artificial Intelligence, 8:99–118, 1977.

    Article  MATH  Google Scholar 

  15. U Montanari. Networks of constraints: Fundamental properties and applications to picture processing. Information Sciences, 7:95–132, 1974.

    Article  MATH  MathSciNet  Google Scholar 

  16. B Nebel. Solving hard qualitative temporal reasoning problems: Evaluating the efficiency of using the ord-horn class. CONSTRAINTS, 1(3):175–190, 1997.

    Article  MATH  MathSciNet  Google Scholar 

  17. G S Tseitin. On the complexity of derivation in propositional calculus. In Structures in the constructive Mathematics and Mathematical logic, pages 115–125. Shsenko, H A O, 1968.

    Google Scholar 

  18. R E Valdés-Pérez. The satisfiability of temporal constraint networks. In Proceedings of the AAAI-87, pages 256–260, Seattle, WA, 1987.

    Google Scholar 

  19. P van Beek. Reasoning about qualitative temporal information. Artificial Intelligence, 58:297–326, 1992.

    Article  MATH  MathSciNet  Google Scholar 

  20. P van Beek and D M Manchak. The design and experimental analysis of algorithms for temporal reasoning. Journal of Artificial Intelligence Research, 4:1–18, 1996.

    Article  MATH  Google Scholar 

  21. M B Vilain and H Kautz. Constraint propagation algorithms for temporal reasoning. In Proceedings AAAI-86, Philadelphia, August 1986.

    Google Scholar 

  22. M B Vilain, H Kautz, and P van Beek. Constraint propagation algorithms for temporal reasoning: A revised report. In Morgan Kaufmann, editor, Readings in Qualitative Reasoning about Physical Systems, pages 373–381, San Mateo, CA, 1990. Revised version of paper that appeared in Proceedings of AAAI-86, 377–382.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Laboratoire d'Informatique de Marseille, Centre de Mathématiques et d'Informatique, 39, rue Joliot Curie, 13453, Marseille cedex 13, France

    BelaÏd Benhamou

  2. School of Computer Studies, University of Leeds, LS2 9JT, Leeds, England

    Amar Isli

Authors
  1. BelaÏd Benhamou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Amar Isli
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Fausto Giunchiglia

Rights and permissions

Reprints and permissions

Copyright information

© 1998 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Benhamou, B., Isli, A. (1998). Study of symmetry in qualitative temporal interval networks. In: Giunchiglia, F. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 1998. Lecture Notes in Computer Science, vol 1480. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0057437

Download citation

  • DOI: https://doi.org/10.1007/BFb0057437

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64993-9

  • Online ISBN: 978-3-540-49793-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation