These papers describe a system that clusters problem-solving traces (AND-trees) into hierarchical clusterings (equivalent in power to sparse AND-OR trees) that are searched on subsequent problems in an attempt to reuse previous experience. The papers offer hypotheses about novice-to-expert transitions as problem solving through categorization relies increasingly on deep (but cost effective) features over naive reliance on surface features. These are a subset of the empirical/analytic hybrid papers.

Fisher, D., & Yoo, J. (1993). "Problem solving, categorization, and concept learning: A unifying view," in G. Nakamura, R. Taraban, & D. Medin (eds.), The Psychology of Learning and Motivation, 29, San Diego, CA: Academic Press, 219--255.

Yoo, J., & Fisher, D. (1991). "Concept Formation over Problem-Solving Experience," in Fisher, D., Pazzani, M., & Langley, P. (eds.), Concept Formation: Experience and Knowledge in Unsupervised Learning. San Mateo, CA: Morgan Kaufmann, 279--306.

Yoo, J., & Fisher, D. (1991). "Concept formation over explanations and problem-solving experiences" Proceedings of the International Joint Conference on Artificial Intelligence, Sydney, Australia: Morgan Kaufmann, 630--636.

A related line of research looked at facilitating efficient reuse and adaptation of means-ends plans through clustering. The gist of this research is well represented in this technical report and culminated in Hua Yang's dissertation (1992).