Abstract. Acquiring adaptation knowledge for case-based reasoning systems is a challenging problem. Such knowledge is typically elicited from domain experts or extracted from the c...
Case-Based Reasoning systems retrieve cases using a similarity function based on the K-NN or some derivatives. These functions are sensitive to irrelevant, interacting or noisy fe...
Adaptation is a task of case-based reasoning systems that is largely domain-dependant. This motivates the study of adaptation knowledge acquisition (AKA) that can be carried out th...
CBR systems are normally used to assist experts in the resolution of problems. During the last few years, researchers have been working in the development of techniques to automate...
Case-based reasoning systems solve new problems by retrieving and adapting the solutions to similar previously solved problems. The success and performance of any case-based reason...
Case-based reasoning systems need to know the limitations of their expertise. Having found the known source cases most relevant to a target problem, they must assess whether those ...
Abstract. Distributed case-based reasoning architectures have the potential to improve the overall performance of case-based reasoning systems. In this paper we describe a collabor...
Abstract. In this paper, we investigate two novel indexing schemes called DHS and D-HS+PSR(II) designed for use in case-based reasoning systems. D-HS is based on a matrix of cases ...
Case-based reasoning systems routinely record the results of prior problem-solving, but not the provenance of new cases: the way in which the new cases were derived. This paper pro...