Maintaining Generalized Arc Consistency on Ad Hoc r-Ary Constraints
CP '08 Proceedings of the 14th international conference on Principles and Practice of Constraint Programming
Efficient constraint propagation engines
ACM Transactions on Programming Languages and Systems (TOPLAS)
Propagation via lazy clause generation
Constraints
Reformulating Global Grammar Constraints
CPAIOR '09 Proceedings of the 6th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Journal of Artificial Intelligence Research
On valued negation normal form formulas
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Efficient reasoning for nogoods in constraint solvers with BDDs
PADL'08 Proceedings of the 10th international conference on Practical aspects of declarative languages
Fast set bounds propagation using a BDD-SAT hybrid
Journal of Artificial Intelligence Research
BDDs for pseudo-boolean constraints: revisited
SAT'11 Proceedings of the 14th international conference on Theory and application of satisfiability testing
MDD propagators with explanation
Constraints
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
A hybrid BDD and SAT finite domain constraint solver
PADL'06 Proceedings of the 8th international conference on Practical Aspects of Declarative Languages
SDD: a new canonical representation of propositional knowledge bases
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
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Smooth decomposable negation normal form (s-DNNF ) circuits are a compact form of representing many Boolean functions, that permit linear time satisfiability checking. Given a constraint defined by an s-DNNF circuit, we can create a propagator for the constraint by decomposing the circuit using a Tseitin transformation. But this introduces many additional Boolean variables, and hides the structure of the original s-DNNF. In this paper we show how we can build a propagator that works on the s-DNNF circuit directly, and can be integrated into a lazy-clause generation-based constraint solver. We show that the resulting propagator can efficiently solve problems where s-DNNF circuits are the natural representation of the constraints of the problem, outperforming the decomposition based approach.