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An Algorithm for Adaptation in Case-based Reasoning

Béatrice Fuchs, Jean Lieber, Alain Mille, Amedeo Napoli

The adaptation process is an important and complex step of case-based reasoning (CBR) and is most of the time designed for a specific application. This article presents a domain-independent algorithm for adaptation in CBR. Cases are mapped to a set of numerical descriptors filled with values and local constraint intervals. The algorithm computes every target solution descriptor by combining a source solution, a matching expressed as variation intervals together with dependencies between the source problem and its solution. It determines for every target solution descriptor an interval of the admissible values in which actual values satisfying global constraints are fixed. This generic approach to adaptation is operational and it introduces general and domain-independant adaptation operators. This study contributes to the design of a general algorithm for adaptation in CBR.

Keywords: Case-Based Reasoning

Citation: Béatrice Fuchs, Jean Lieber, Alain Mille, Amedeo Napoli: An Algorithm for Adaptation in Case-based Reasoning. In W.Horn (ed.): ECAI2000, Proceedings of the 14th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2000, pp.45-49.


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ECAI-2000 is organised by the European Coordinating Committee for Artificial Intelligence (ECCAI) and hosted by the Humboldt University on behalf of Gesellschaft für Informatik.