Constraint Processing
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
An optimal coarse-grained arc consistency algorithm
Artificial Intelligence
Generalizing constraint satisfaction on trees: Hybrid tractability and variable elimination
Artificial Intelligence
Watched literals for constraint propagation in minion
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
Tractable triangles and cross-free convexity in discrete optimisation
Journal of Artificial Intelligence Research
The tractability of CSP classes defined by forbidden patterns
Journal of Artificial Intelligence Research
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A variable elimination rule allows the polynomial-time identification of certain variables whose elimination does not affect the satisfiability of an instance. Variable elimination in the constraint satisfaction problem (CSP) can be used in preprocessing or during search to reduce search space size. We show that there are essentially just four variable elimination rules defined by forbidding generic sub-instances, known as irreducible patterns, in arc-consistent CSP instances. One of these rules is the Broken Triangle Property, whereas the other three are novel.