Symmetry breaking via LexLeader feasibility checkers

  • Authors:

  • Justin Yip;Pascal Van Hentenryck

  • Affiliations:

  • Brown University, Providence, RI;Brown University, Providence, RI

  • Venue:
  • IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
  • Year:
  • 2011

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Abstract

This paper considers matrix models, a class of CSPs which generally exhibit significant symmetries. It proposed the idea of LexLeader feasibility checkers that verify, during search, whether the current partial assignment can be extended into a canonical solution. The feasibility checkers are based on a novel result by [Katsirelos et al., 2010] on how to check efficiently whether a solution is canonical. The paper generalizes this result to partial assignments, various variable orderings, and value symmetries. Empirical results on 5 standard benchmarks shows that feasibility checkers may bring significant performance gains, when jointly used with DOUBLELEX or SNAKELEX.