In Proceedings of the Fifth National Conference on Artificial Intelligence (AAAI), pp. 551-555, Philadelphia, PA, August 1986.
Paper ID: 206
Category: Explanation-Based Learning
A domain independent technique for generalizing a broad class of explanations is described. This method is compared and contrasted with other approaches to generalizing explanations, including an abstract version of the algorithm used in the STRIPS system and the EBG technique developed by Mitchell, Keller, and Kedar-Cabelli. We have tested this generalization technique on a number of examples in different domains, and present detailed descriptions of several of these.
