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Index Transformation Techniques for Facilitating Creative Use of Multiple Cases

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Proceedings of the Twelfth International Joint Conference on Artificial Intelligence. Cognitive Modeling. Pages 347-351.

Abstract

Using cases to find innovative solutions to problems is mainly the result of two processes: (1) cross-contextual remindings, and (2) composition of multiple cases or case parts. Although the ability to use cases taken from across contextual boundaries is desirable, there is a tension between representing and accessing cases across contexts and in.using parts of multiple cases to synthesize a solution. One way of alleviating this difficulty is through index transformation. In this paper, we represent two index transformation techniques that facilitate both cross-contextual remindings and the access of multiple appropriate case parts. The mechanisms are general and principled (based on a qualitative calculus). They are also behaviorpreserving, a needed requirement for case synthesis in many domains of interest. The transformation techniques have been implemented in CADET, a case-based problem solver that operates in the domain of mechanical design.

Katia P. Sycara, and Dundee Navinchandra. 1991. Index Transformation Techniques for Facilitating Creative Use of Multiple Cases. In Proceedings of the Twelfth International Joint Conference on Artificial Intelligence, IJCAI-91. IJCAI, 347–351. https://ijcai.org/proceedings/1991/52
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