Generalizing on Multiple Grounds: Performance Learning in Model- Based Technology

Authors:
Paul Resnick
Affiliations:
-
Venue:
Generalizing on Multiple Grounds: Performance Learning in Model- Based Technology
Year:
1989

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Diagnosing tree-decomposable circuits

IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2

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Abstract

This thesis explores ways to augment a model-based diagnostic program with a learning component, so that it speeds up as it solves problems. Several learning components are proposed, each exploiting a different kind of similarity between diagnostic examples. Through analysis and experiments, we explore the effect each learning component has on the performance of a model-based diagnostic program. We also analyze more abstractly the performance effects of Explanation-Based Generalization, a technology that is used in several of the proposed learning components.