Communications of the ACM - Special issue on parallelism
An architecture for understanding in planning, action, and learning
ACM SIGART Bulletin
Dynamic Memory: A Theory of Reminding and Learning in Computers and People
Dynamic Memory: A Theory of Reminding and Learning in Computers and People
Case-based representations for procedural knowledge
Case-based representations for procedural knowledge
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Case-based reasoning refers to the class of memory-based problem solving methods which emphasize the adaptation of recalled solutions (explanations, diagnoses, plans) over the generation of solutions from first principles. CBR has become a popular methodology, resulting in a proliferation of case organization and representation proposals. The goal of this paper is to sort through some of these proposals. Using the formal models of "procedure" and "case-based reasoning" introduced in Zito-Wolf and Alterman (1992), we compare three current proposals for the organization of procedural case-bases: individual cases, microcases, and multi cases. We give a worst-case analysis that shows the advantages of the multi case in terms of case storage and retrieval costs. The model predicts that multi cases reduce case storage and retrieval costs as compared to the other two models. We then provide some empirical evidence from an implemented system that suggests that the trends observed in the formal model are also observable in case bases of practical size.