Competence guided incremental footprint-based retrieval

Case-based reasoning (CBR) systems solve new problems by retrieving and ada pting problem solving experiences stored as cases in a case-base. Success d epends largely on the performance of the case retrieval algorithm used. Smy th and McKenna [Lecture Notes in Artificial Intelligence LNAI 1650 (1999) 3 43-357] have described a novel retrieval technique, called footprint-based retrieval (FBR), which is guided by a model of case competence. FBR as it s tands benefits from superior efficiency characteristics and achieves near-o ptimal competence and quality characteristics. In this paper, we describe a simple but important extension to FBR. Empirically we show that this new a lgorithm can deliver optimal retrieval performance while at the same time r etaining the efficiency benefits of the original FBR method. (C) 2001 Elsev ier Science B.V. All rights reserved.