The hazards of fancy backtracking
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Generalizing partial order and dynamic backtracking
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Contradicting Conventional Wisdom in Constraint Satisfaction
PPCP '94 Proceedings of the Second International Workshop on Principles and Practice of Constraint Programming
Arc-Consistency in Dynamic CSPs Is No More Prohibitive
ICTAI '96 Proceedings of the 8th International Conference on Tools with Artificial Intelligence
Journal of Artificial Intelligence Research
Using CSP look-back techniques to solve real-world SAT instances
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
A complexity analysis of space-bounded learning algorithms for the constraint satisfaction problem
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Conflict-Based Repair Techniques for Solving Dynamic Scheduling Problems
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
CSCLP'09 Proceedings of the 14th Annual ERCIM international conference on Constraint solving and constraint logic programming
Explaining the cumulative propagator
Constraints
A hybrid BDD and SAT finite domain constraint solver
PADL'06 Proceedings of the 8th international conference on Practical Aspects of Declarative Languages
Lazy explanations for constraint propagators
PADL'10 Proceedings of the 12th international conference on Practical Aspects of Declarative Languages
Identifying and exploiting problem structures using explanation-based constraint programming
CPAIOR'05 Proceedings of the Second international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
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Most of complete search algorithms over Constraint Satisfaction Problems (csp) are based on Standard Backtracking. Two main enhancements of this basic scheme have been studied: first, to integrate constraint propagation as mac which maintains arc consistency during search; second, intelligent backtrackers which avoid repeatedly falling in the same dead-ends by recording nogoods as Conflict-directed BackJumping (cbj) or Dynamic Backtracking (dbt). Integrations of constraint propagation within intelligent backtrackers have been done as mac-cbj which maintains arc consistency in cbj. However, Bessière and RÉgin have shown that mac-cbj was very rarely better than mac. However, the inadequacy of mac-cbj is more related to the fact that cbj does not avoid thrashing than to the cost of the management of nogoods. This paper describes and evaluates mac-dbt which maintains arc-consistency in dbt. Experiments show that mac-dbt is able to solve very large problems and that it remains very stable as the size of the problems increases. Moreover, mac-dbt outperforms mac on the structured problems we have randomly generated.