Concurrent constraint programming
Concurrent constraint programming
A filtering algorithm for constraints of difference in CSPs
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
A Sufficient Condition for Backtrack-Free Search
Journal of the ACM (JACM)
Communications of the ACM
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
Global Constraints for Lexicographic Orderings
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Propagating logical combinations of constraints
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Dynamic variable elimination during propagation solving
Proceedings of the 10th international ACM SIGPLAN conference on Principles and practice of declarative programming
MiniZinc: towards a standard CP modelling language
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Implementing logical connectives in constraint programming
Artificial Intelligence
Half reification and flattening
CP'11 Proceedings of the 17th international conference on Principles and practice of constraint programming
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Constraint propagation algorithms implement logical inference. For efficiency, it is essential to control whether and in what order basic inference steps are taken. We provide a high-level framework that clearly differentiates between information needed for controlling propagation versus that needed for the logical semantics of complex constraints composed from primitive ones. We argue for the appropriateness of our controlled propagation framework by showing that it captures the underlying principles of manually designed propagation algorithms, such as literal watching for unit clause propagation and the lexicographic ordering constraint. We provide an implementation and benchmark results that demonstrate the practicality and efficiency of our framework.