The Case for Structure - basedRepresentationsKathryn

Case-based reasoning involves reasoning from cases: speciic pieces of experience , the reasoner's or another's, that can be used to solve problems. As a result, case representation is critical: an incomplete case representation limits the system's reasoning power. In this paper we argue for structure-based case representations, which express arbitrary relations among objects in a exible way, over more limited or innexible methods. We motivate the distinction between these kinds of representations with examples from information retrieval systems, CBR systems, and computational models of human analogical reasoning. Structure-based representations provide the beneets of greater expres-sivity and economy. We give examples of these beneets from two case-based planning systems we have developed, CaPER and CHIRON, and show how the case matching and case acquisition costs can be reduced through the use of massively parallel techniques. This paper is being submitted as a scientiic paper.