Contradicting Conventional Wisdom in Constraint Satisfaction
PPCP '94 Proceedings of the Second International Workshop on Principles and Practice of Constraint Programming
Constraint Processing
About the use of local consistency in solving CSPs
ICTAI '00 Proceedings of the 12th IEEE International Conference on Tools with Artificial Intelligence
Optimal and suboptimal singleton arc consistency algorithms
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Theoretical analysis of singleton arc consistency and its extensions
Artificial Intelligence
Optimization of Simple Tabular Reduction for Table Constraints
CP '08 Proceedings of the 14th international conference on Principles and Practice of Constraint Programming
On the Integration of Singleton Consistencies and Look-Ahead Heuristics
Recent Advances in Constraints
Constraint-Level Advice for Shaving
ICLP '08 Proceedings of the 24th International Conference on Logic Programming
Beyond Singleton Arc Consistency
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
A study of residual supports in arc consistency
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Probabilistic consistency boosts MAC and SAC
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Extracting microstructure in binary constraint networks
CSCLP'06 Proceedings of the constraint solving and contraint logic programming 11th annual ERCIM international conference on Recent advances in constraints
Developing approaches for solving a telecommunications feature subscription problem
Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research
Generalized arc consistency for positive table constraints
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
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In this paper, we propose a new approach to establish Singleton Arc Consistency (SAC) on constraint networks. While the principle of existing SAC algorithms involves performing a breadth-first search up to a depth equal to 1, the principle of the two algorithms introduced in this paper involves performing several runs of a greedy search (where at each step, arc consistency is maintained). It is then an original illustration of applying inference (i.e. establishing singleton arc consistency) by search. Using a greedy search allows benefiting from the incrementality of arc consistency, learning relevant information from conflicts and, potentially finding solution(s) during the inference process. Further-more, both space and time complexities are quite competitive.