Generalization for Explanation-Based Schema Acquisition

This paper is about explanation-based learning for heuristic problem solvers which "build" solutions using schemata (frames like scripts) as both "bricks" and "mortar". The heart of the paper is a description of a generalization method which is designed to extract as much information as possible from examples of successful problem solving behavior. A related generalizer, (less powerful but more efficient), has been implemented as part of an experimental apprentice.