Abstract
The search space of constraint satisfaction problems (CSPs) can be reduced by using value interchangeability. This notion consists of aggregating subsets of values that behave similarly on the future branches of the search. BT-CPR [8], is a typical backtracking algorithm using value interchangeability. It uses the Cartesian product representation of the search space (CPR) which aggregates partial solutions and proves particularly useful for finding and representing all solutions of a CSP. It is assessed that maintaining arc-consistency (MAC) is the most efficient general algorithm for solving hard problems. A few work on combining MAC with CPR exists. In this paper we study comparatively two other possible alternatives of MAC-CPR.
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References
Bessiére C., Freuder E.C., and Régin J.-C.: Using constraint metaknowledge to reduce arc consistency computation. AI, (107):125–148, 99
Bessiére C. and Régin J.-C.: MAC and combined heuristics: Two reasons to forsake FC(and CBJ?) on hard problems. In CP96, pages 61–75. CP, 96
Bliek C.: Generalizing partial order and dynamic backtracking. In AAAI-98 Proceedings, pages 319–325, Madison, Wisconsin, July 98. AAAI
Choueiry B.Y. and Noubir G.: On the computation of local interchangeability in discrete constraint satisfaction problems. Technical Report KSL-98-24, Standford, 98
Freuder E.C.: Eliminating interchangeable values in constraint satisfaction problems. In Proceedings of AAAI’91, pages 227–233, 91
Ginsberg M. and McAllester D.: Gsat and dynamic backtracking. In J. Doyle, editor, Proceedings of the 4th IC on PKRR, pages 226–237. KR, 94
Haselböck A.: Exploiting interchangeabilities in constraint satisfaction problems. In Proceedings of IJCAI’93, pages 282–287, 93
Hubbe P.D. and Freuder E.C.: An efficient cross product representation of the constraint satisfaction problem search space. In Proc. of AAAI-92, pages 421–427, July 92
Kondrak G.: A theoretical evaluation of selected backtracking algorithms. Master’s thesis, Univ. of Alberta, 94
Lesaint D.: Maximal Sets of Solutions for Constraint Satisfaction Problems. In A. Cohn, editor, Proceedings of ECAI’94, pages 110–114. John Wiley & Sons, Ltd, 94
Sabin D. and Freuder E.C.: Contradicting conventional wisdom in constraint satisfaction. In Proceedings ECAI-94, pages 125–129, 94
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© 2000 Springer-Verlag Berlin Heidelberg
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Silaghi, MC., Sam-Haroud, D., Faltings, B. (2000). Ways of Maintaining Arc Consistency in Search Using the Cartesian Representation. In: Apt, K.R., Monfroy, E., Kakas, A.C., Rossi, F. (eds) New Trends in Constraints. WC 1999. Lecture Notes in Computer Science(), vol 1865. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44654-0_9
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DOI: https://doi.org/10.1007/3-540-44654-0_9
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