Dual viewpoint heuristics for binary constraint satisfaction problems
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Beyond NP: Arc-Consistency for Quantified Constraints
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Solving quantified constraint satisfaction problems
Artificial Intelligence
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
QCSP made practical by virtue of restricted quantification
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
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The Quantified Constraint Satisfaction Problem (QCSP) has been introduced to express situations in which we are not able to control the value of some of the variables (the universal ones). Despite the expressiveness of QCSP, many problems, such as two-players games or motion planning of robots, remain difficult to express. Two more modeler-friendly frameworks have been proposed to handle this difficulty, the Strategic CSP and the QCSP+. We define what we name back-propagation on QCSP+. We show how back-propagation can be used to define a goal-driven value ordering heuristic and we present experimental results on board games.