Explanation-based failure recovery

Authors:
Ajay Gupta
Affiliations:
Hewlett-Packard Laboratories, Bristol, UK
Venue:
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 2
Year:
1987

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Abstract

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.