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.
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