Proceedings of the Annual Meeting of the Cognitive Science Society

A model of case-based reasoning is presented that relies on a procedural representation for cases. In an implementation of this model, cases are represented as knowledge sources in a blackboard architecture. Case knowledge sources define local neighborhoods of similarity and are triggered if a problem case falls within a neighborhood. This form of "local indexing" is a viable alternative where global similarity metrics are unavailable. Other features of this approach include the potential for fine-grained scheduling of case retrieval, a uniform representation for cases and other knowledge sources in hybrid systems that incorporate case-based reasoning and other reasoning methods, and a straightforward way to represent the actions generated by cases. This model of case-based reasoning has been implemented in a prototype system ("Broadway") that selects from a case base automobiles that meet a car buyer's requirements most closely and explains its selections.