Abstract
What makes a good consistency? Depending on the constraint, it may be a good pruning power or a low computational cost. By using machine learning techniques (search in an hypothesis space and clustering), we propose to define new automatically generated solvers which form a sequence of consistencies intermediate between bound- and arc-consistency.
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Lallouet, A., Legtchenko, A., Dao, TBH., Ed-Dbali, A. (2003). Intermediate (Learned) Consistencies. In: Rossi, F. (eds) Principles and Practice of Constraint Programming – CP 2003. CP 2003. Lecture Notes in Computer Science, vol 2833. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45193-8_73
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DOI: https://doi.org/10.1007/978-3-540-45193-8_73
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20202-8
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