Learning efficient rules by maintaining the explanation structure
Jihie Kim, Paul S. Rosenbloom · 1996
Many learning systems suffer from the utility problem; that is, that time after learning is greater than time before learning. Discovering how to assure that learned knowledge will in fact speed up system performance has been a focus of research in explanation-based learning (EBL). One way to analyze the utility problem is by examining the differences between the match process (match search) of the learned rule and the problem-solving process from which it is learned. Prior work along these lines examined one such difference. It showed that if the search-control knowledge used during problem solving is not maintained in the match process for learned rules, then learning can engender a slowdown; but that this slowdown could be eliminated if the match is constrained by the original search-control knowledge. This article examines a second difference --- when the structure of the problem solving differs from the structure of the match process for the learned rules, time after learning can ...