Proceedings of the Annual Meeting of the Cognitive Science Society

Learning from problem solving episodes has previously been modeled in two different ways: Case- based planners ( H a m m o n d , 1989) acquire additional knowledge by storing n e w cases (i.e. the specific plans for different problems); search-based systems like S O A R or P R O D I G Y learn by chunking the result of a search process (Rosenbloom eL al., 1991; Minton et. al., 1989) and by forming macro- operators (Korf, 1985). This paper proposes comprehension-based learning as a third possibility: From specific problem solving experiences (cases) and a related problem description (text) some coarse- grained abstract representation is constructed, that m a y initially be inconsistent and redundant. B y wholistic integration processes a coherent and consistent procedure schema is subsequently formed. Such a procedure schema can be reused for obtaining solutions to jH-oblems which are quite different at the concrete level, but have been comprehended to share abstract commonalties. T h e acquisition of such a procedure schema is exemplified for various solutions to different Tower of Hanoi problems (3-, 4-, and 5- disks). T h e utilization of these schemata is then discussed for the 4-disk problem and respective experimental data are reported.