Proceedings of the Annual Meeting of the Cognitive Science Society

In domains requiring complex relational representations, simply expressing a new problem may be a complex, error-prone, and time-consuming task. This paper presents an approach to problem formulation, termed case-based formulation (CBF), that uses previous cases as a model and a guide for expressing new cases. By expressing new problems in terms of old, C B F can potentially increase the speed and accuracy of problem formulation, reduce the computational expense of retrieval, and determine the relevant similarities and differences between a new case and and the most similar old cases as a side-effect of expressing the new case. Three forms of C B F can be distinguished by the extent to which the retrieval and adaptation of previous cases are automated and the extent to which the facts of multiple cases Can be combined. A n initial implementation of one form of C B F is described and its ability to use previous cases to increase the efficiency and accuracy of new-case formalization is illustrated with a complex relational case.