Partition search for non-binary constraint satisfaction
Information Sciences: an International Journal
Search Strategies for Rectangle Packing
CP '08 Proceedings of the 14th international conference on Principles and Practice of Constraint Programming
Hardness of Minimizing and Learning DNF Expressions
FOCS '08 Proceedings of the 2008 49th Annual IEEE Symposium on Foundations of Computer Science
MINION: A Fast, Scalable, Constraint Solver
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
An optimal coarse-grained arc consistency algorithm
Artificial Intelligence
A compression algorithm for large arity extensional constraints
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Implementing logical connectives in constraint programming
Artificial Intelligence
Generating special-purpose stateless propagators for arbitrary constraints
CP'10 Proceedings of the 16th international conference on Principles and practice of constraint programming
Watched literals for constraint propagation in minion
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
Exploiting short supports for generalised arc consistency for arbitrary constraints
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
Short and long supports for constraint propagation
Journal of Artificial Intelligence Research
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Constraint propagation is one of the key techniques in constraint programming, and a large body of work has built up around it. Special-purpose constraint propagation algorithms frequently make implicit use of short supports -- by examining a subset of the variables, they can infer support (a justification that a variable-value pair still forms part of a solution to the constraint) for all other variables and values and save substantial work. Recently short supports have been used in general purpose propagators, and (when the constraint is amenable to short supports) speed ups of more than three orders of magnitude have been demonstrated. In this paper we present SHORTSTR2, a development of the Simple Tabular Reduction algorithm STR2+. We show that SHORTSTR2 is complementary to the existing algorithms SHORTGAC and HAGGISGAC that exploit short supports, while being much simpler. When a constraint is amenable to short supports, the short support set can be exponentially smaller than the full-length support set. Therefore SHORTSTR2 can efficiently propagate many constraints that STR2+ cannot even load into memory. We also show that SHORTSTR2 can be combined with a simple algorithm to identify short supports from full-length supports, to provide a superior drop-in replacement for STR2+.