Exploiting past and future: pruning by inconsistent partial state dominance

  • Authors:

  • Christophe Lecoutre;Lakhdar Sais;Sébastien Tabary;Vincent Vidal

  • Affiliations:

  • CRIL, CNRS, FRE, Lens cedex, France;CRIL, CNRS, FRE, Lens cedex, France;CRIL, CNRS, FRE, Lens cedex, France;CRIL, CNRS, FRE, Lens cedex, France

  • Venue:
  • CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
  • Year:
  • 2007

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Abstract

It has recently been shown, for the Constraint Satisfaction Problem (CSP), that the state associated with a node of the search tree built by a backtracking algorithm can be exploited, using a transposition table, to prevent the exploration of similar nodes. This technique is commonly used in game search algorithms, heuristic search or planning. Its application is made possible in CSP by computing a partial state - a set of meaningful variables and their associated domains - preserving relevant information. We go further in this paper by providing two new powerful operators dedicated to the extraction of inconsistent partial states. The first one eliminates any variable whose current domain can be deduced from the partial state, and the second one extracts the variables involved in the inconsistency proof of the subtree rooted by the current node. Interestingly, we show these two operators can be safely combined, and that the pruning capabilities of the recorded partial states can be improved by a dominance detection approach (using lazy data structures).