A filtering algorithm for constraints of difference in CSPs
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Comparing trailing and copying for constraint programming
Proceedings of the 1999 international conference on Logic programming
Chaff: engineering an efficient SAT solver
Proceedings of the 38th annual Design Automation Conference
An Open-Ended Finite Domain Constraint Solver
PLILP '97 Proceedings of the9th International Symposium on Programming Languages: Implementations, Logics, and Programs: Including a Special Trach on Declarative Programming Languages in Education
Search Procedures and Parallelism in Constraint Programming
CP '99 Proceedings of the 5th International Conference on Principles and Practice of Constraint Programming
Components for State Restoration in Tree Search
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
A decomposition-based implementation of search strategies
ACM Transactions on Computational Logic (TOCL)
Constraint Logic Programming using Eclipse
Constraint Logic Programming using Eclipse
Efficient constraint propagation engines
ACM Transactions on Programming Languages and Systems (TOPLAS)
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
Programming constraint services: high-level programming of standard and new constraint services
Programming constraint services: high-level programming of standard and new constraint services
Watched literals for constraint propagation in minion
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
An automated approach to generating efficient constraint solvers
Proceedings of the 34th International Conference on Software Engineering
Improving the performance of FD constraint solving in a CFLP system
FLOPS'12 Proceedings of the 11th international conference on Functional and Logic Programming
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Constraint propagation solvers interleave propagation, removing impossible values from variable domains, with search. The solver state is modified during propagation. But search requires the solver to return to a previous state. Hence a propagation solver must determine how to maintain state during propagation and forward and backward search. This paper sets out the possible ways in which a propagation solver can choose to maintain state, and the restrictions that such choices place on the resulting system. Experiments illustrate the result of various choices for the three principle state components of a solver: variables, propagators, and dependencies between them. This paper also provides the first realistic comparison of trailing versus copying for state restoration.