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Constraint-directed backtracking

  • Constraint Satisfaction and Scheduling
  • Conference paper
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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1342))

Abstract

We propose a new backtracking algorithm called constraint- directed backtracking (CDBT) for solving general constraint-satisfaction problems (CSPs). CDBT searches for an assignment to variables in a variable set from a given constraint posed on that variable set and appends it to an existing partial solution, in contrast with the naive backtracking (BT) which searches for an assignment of one variable from its domain. In this way, CDBT has a more limited search space and it actually visits fewer nodes than BT. Like BT, CDBT can be improved by incorporating other tree seach techniques such as backjumping or forward checking and consistency techniques such as the ω-consistency algorithm.[/ p]

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References

  1. J. R. Bitner and E. M. Reingold. Backtrack programming techniques. Communications of the ACM, 18(11):651–656, 1975.

    Article  Google Scholar 

  2. R. Dechter and J. Pearl. Tree clustering for constraint networks. Artificial Intelligence, 38:353–366, 1989.

    Article  Google Scholar 

  3. J. Gaschnig. A general backtrack algorithm that eliminates most redundant tests. In Proceedings of IJCAI-77, page 457, Cambridge, MA, 1977.

    Google Scholar 

  4. S. W. Golomb and L. D. Baumert. Backtrack programming. Journal of the ACM, 12(4):516–524, 1965.

    Article  Google Scholar 

  5. M. Gyssens, P. G. Jeavons, and D. A. Cohen. Decomposing constraint satisfaction problems using database techniques. Artificial Intelligence, 66:57–89, 1994.

    Article  Google Scholar 

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

    Article  Google Scholar 

  7. G. Kondrak and P. van Beek. A theoretical evaluation of selected backtracking algorithms. In Proceedings of IJCAI-95, pages 541–547, Montreal, Canada, 1995.

    Google Scholar 

  8. W. Pang. Constraint-Directed Approach for Analyzing and Solving General Constraint Satisfaction Problems. PhD thesis, University of Regina, Saskatchewan, Canada, 1997.

    Google Scholar 

  9. W. Pang and S. D. Goodwin. A revised sufficient condition for backtrack-free search. In Proceedings of 10th Florida AI Research Symposium, pages 52–56, Daytona Beach, FL, May 1997.

    Google Scholar 

  10. P. Prosser. Hybrid algorithms for the constrain satisfaction problem. Computational Intelligence, 9(3):268–299, 1993.

    Google Scholar 

  11. E. Tsang. Foundations of Constraint Satisfaction. Academic Press, San Diego, CA, 1993.

    Google Scholar 

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Abdul Sattar

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© 1997 Springer-Verlag Berlin Heidelberg

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Pang, W., Goodwin, S.D. (1997). Constraint-directed backtracking. In: Sattar, A. (eds) Advanced Topics in Artificial Intelligence. AI 1997. Lecture Notes in Computer Science, vol 1342. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63797-4_57

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  • DOI: https://doi.org/10.1007/3-540-63797-4_57

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63797-4

  • Online ISBN: 978-3-540-69649-0

  • eBook Packages: Springer Book Archive

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