Arc and path consistence revisited
Artificial Intelligence
Network-based heuristics for constraint-satisfaction problems
Artificial Intelligence
Arc consistency for factorable relations
Artificial Intelligence
A generic arc-consistency algorithm and its specializations
Artificial Intelligence
Arc-consistency and arc-consistency again
Artificial Intelligence
Using constraint metaknowledge to reduce arc consistency computation
Artificial Intelligence
Radio Link Frequency Assignment
Constraints
Contradicting Conventional Wisdom in Constraint Satisfaction
PPCP '94 Proceedings of the Second International Workshop on Principles and Practice of Constraint Programming
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 2
Why AC-3 is almost always better than AC-4 for establishing arc consistency in CSPs
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Using inference to reduce arc consistency computation
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Refining the basic constraint propagation algorithm
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Making AC-3 an optimal algorithm
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Search Space Reduction for Constraint Optimization Problems
CP '08 Proceedings of the 14th international conference on Principles and Practice of Constraint Programming
Efficient Algorithms for Functional Constraints
ICLP '08 Proceedings of the 24th International Conference on Logic Programming
ICLP '09 Proceedings of the 25th International Conference on Logic Programming
Reasoning from last conflict(s) in constraint programming
Artificial Intelligence
AC3-OP: An Arc-Consistency Algorithm for Arithmetic Constraints
Proceedings of the 2009 conference on Artificial Intelligence Research and Development: Proceedings of the 12th International Conference of the Catalan Association for Artificial Intelligence
Advisors for incremental propagation
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Path consistency by dual consistency
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Relational consistency by constraint filtering
Proceedings of the 2010 ACM Symposium on Applied Computing
Improving the performance of maxRPC
CP'10 Proceedings of the 16th international conference on Principles and practice of constraint programming
Generating special-purpose stateless propagators for arbitrary constraints
CP'10 Proceedings of the 16th international conference on Principles and practice of constraint programming
Evaluating and Improving Modern Variable and Revision Ordering Strategies in CSPs
Fundamenta Informaticae - RCRA 2008 Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion
Bit-vector algorithms for binary constraint satisfaction and subgraph isomorphism
Journal of Experimental Algorithmics (JEA)
AC2001-OP: an arc-consistency algorithm for constraint satisfaction problems
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
Solving functional constraints by variable substitution
Theory and Practice of Logic Programming
Computers and Industrial Engineering
A CSP solver focusing on FAC variables
CP'11 Proceedings of the 17th international conference on Principles and practice of constraint programming
Algorithms for stochastic CSPs
CP'06 Proceedings of the 12th 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
Generalized arc consistency for positive table constraints
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
A fine-grained arc-consistency algorithm for non-normalized constraint satisfaction problems
International Journal of Applied Mathematics and Computer Science
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
Extending generalized arc consistency
SETN'12 Proceedings of the 7th Hellenic conference on Artificial Intelligence: theories and applications
Managing dynamic CSPs with preferences
Applied Intelligence
Managing qualitative preferences with constraints
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
The tractability of CSP classes defined by forbidden patterns
Journal of Artificial Intelligence Research
Domain consistency with forbidden values
Constraints
Short and long supports for constraint propagation
Journal of Artificial Intelligence Research
Variable elimination in binary CSP via forbidden patterns
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Extending simple tabular reduction with short supports
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Optimal implementation of watched literals and more general techniques
Journal of Artificial Intelligence Research
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The use of constraint propagation is the main feature of any constraint solver. It is thus of prime importance to manage the propagation in an efficient and effective fashion. There are two classes of propagation algorithms for general constraints: fine-grained algorithms where the removal of a value for a variable will be propagated to the corresponding values for other variables, and coarse-grained algorithms where the removal of a value will be propagated to the related variables. One big advantage of coarse-grained algorithms, like AC-3, over fine-grained algorithms, like AC-4, is the ease of integration when implementing an algorithm in a constraint solver. However, fine-grained algorithms usually have optimal worst case time complexity while coarse-grained algorithms do not. For example, AC-3 is an algorithm with non-optimal worst case complexity although it is simple, efficient in practice, and widely used. In this paper we propose a coarse-grained algorithm, AC2001/3.1, that is worst case optimal and preserves as much as possible the ease of its integration into a solver (no heavy data structure to be maintained during search). Experimental results show that AC2001/3.1 is competitive with the best fine-grained algorithms such as AC-6. The idea behind the new algorithm can immediately be applied to obtain a path consistency algorithm that has the best-known time and space complexity. The same idea is then extended to non-binary constraints.