A theory of diagnosis from first principles
Artificial Intelligence
Consistency restoriation and explanations in dynamic CSPs----application to configuration
Artificial Intelligence
QUICKXPLAIN: preferred explanations and relaxations for over-constrained problems
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
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Interactive tasks such as online configuration can be modeled as constraint satisfaction problems. These can be solved interactively by a user assigning values to variables. Explanations for failure in constraint programming tend to focus on conflict. However, what is often desirable is an explanation that is corrective in the sense that it provides the basis for moving forward in the problem-solving process. This paper defines this notion of corrective explanation and demonstrates that a greedy search approach performs very well on a large real-world configuration problem.