Competence guided incremental footprint-based retrieval

Case-based reasoning (CBR) systems solve new problems by retrieving and adapting problem solving experiences stored as cases in a case-base. Success depends largely on the performance of the case retrieval algorithm used. Smyth and McKenna [Lecture Notes in Arti®cial Intelligence LNAI 1650 (1999) 343±357] have described a novel retrieval technique, called footprint-based retrieval (FBR), which is guided by a model of case competence. FBR as it stands bene®ts from superior ef®ciency characteristics and achieves near-optimal competence and quality characteristics. In this paper, we describe a simple but important extension to FBR. Empirically we show that this new algorithm can deliver optimal retrieval performance while at the same time retaining the ef®ciency bene®ts of the original FBR method. q 2001 Elsevier Science B.V. All rights reserved.