Tree clustering for constraint networks (research note)
Artificial Intelligence
The vertex separation and search number of a graph
Information and Computation
Compiling constraint satisfaction problems
Artificial Intelligence
Consistency restoriation and explanations in dynamic CSPs----application to configuration
Artificial Intelligence
A survey of graph layout problems
ACM Computing Surveys (CSUR)
Product Configuration Frameworks-A Survey
IEEE Intelligent Systems
An overview of knowledge‐based configuration
AI Communications
A survey on knowledge compilation
AI Communications
A perspective on knowledge compilation
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
SPUDD: stochastic planning using decision diagrams
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
AND/OR search spaces for graphical models
Artificial Intelligence
AND/OR Multi-valued Decision Diagrams for Constraint Networks
Concurrency, Graphs and Models
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Knowledge compilation properties of tree-of-BDDs
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
AND/OR multi-valued decision diagrams (AOMDDs) for graphical models
Journal of Artificial Intelligence Research
AND/OR multi-valued decision diagrams for constraint optimization
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Interactive cost configuration over decision diagrams
Journal of Artificial Intelligence Research
Compiling constraint networks into AND/OR multi-valued decision diagrams (AOMDDs)
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
Integrating CSP decomposition techniques and BDDs for compiling configuration problems
CPAIOR'05 Proceedings of the Second international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Representing CSPs with set-labeled diagrams: a compilation map
GKR'11 Proceedings of the Second international conference on Graph Structures for Knowledge Representation and Reasoning
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Constraint programming techniques are widely used to model and solve decision problems and many algorithms have been developed to solve automatically and efficiently families of CSPs; nevertheless, they do not help solve interactive decision support problems, like product configuration. In such problems, the user chooses the values of the variables, and the role of the system is not to solve the CSP, but to help the user in this task. Dynamic global consistency maintaining is one of the most useful functionalities that should be offered by such a CSP platform. Unfortunately, this task is intractable in the worst case. Since interactivity requires short response times, intractability must be circumvented some way. To this end, compilation methods have been proposed that transform the original problem into a data structure allowing a short response time. In this paper, we extend the work of Amilhastre et al. [1] and Vempaty [15] by the use of a new structure, tree-driven automata, that takes advantage of the structural characteristics of configuration problems (decomposition of the components into independent subcomponents). Tree-driven automata can be far more compact than classical automata while keeping their good properties, especially a tractable complexity for the maintenance of global consistency.