Artificial Intelligence
Explanation-Based Generalization: A Unifying View
Machine Learning
Explanation-Based Learning: An Alternative View
Machine Learning
Planning with constraints
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 2
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Interactions are inherent in design-type problem-solving tasks where only partially compiled operators are available. Failures arising from such interactions can best be recovered by explaining them in the underlying domain models. In this paper we explain how Explanation-Based Learning provides a framework for recovering in this manner. This approach also alleviates some of the problems associated with the least-commitment approach to design-type problem-solving.