Fuzzy Logic for the Retrieval Step of a Case-Based Reasoner

This paper presents an original use of fuzzy logic for the design of Case-Based Reasoning (CBR) assistants, mainly for the case retrieval step. Our motivation comes from the importance of allowing for the expression of exible data (incomplete and imprecise data, preferences) in problem and case descriptions and to manage them in case retrieval. We present our retrieval system CAREFUL based on possibility theory that takes into account this exibility. For an eecient retrieval , we have adapted a hierarchical fuzzy classiication algorithm for case ltering. This step can also be used to help the user to describe the problem, and enable him to specify its own similarity for each problem attribute. We have also adapted fuzzy pattern matching techniques in order to execute the selection step. Before comparing our approach to some related CBR works and concluding, we illustrate our system in a simple example.