15th European Conference on Artificial Intelligence
  July 21-26 2002     Lyon     France  
   

ECAI-2002 Conference Paper

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Strong, Fuzzy and Smooth Hierarchical Classification for Case-Based Problem Solving

Jean Lieber

This paper explains how case-based problem solving can have benefit from a hierarchical organisation of problems based on a generality relation. Three adaptation-guided retrieval processes are described. The strong classification in a problem hierarchy is a classical deductive process. It is based on the generality relation between problems which organises the hierarchy. The fuzzy classification is a fuzzification of the strong classification. It is based on a fuzzy generality relation between problems, which can be seen as a non-symmetrical similarity measure. The smooth classification extends the fuzzy classification: it is also based on a similarity or dissimilarity measure but takes into account problem and solution adaptation knowledge. These processes have been successfully implemented in two case-based reasoning systems: Resyn/CBR in the domain of organic synthesis and Kasimir/CBR in the domain of cancer treatment.

Keywords: Case-Based Reasoning, Reuse of Knowledge, Automated Reasoning, Knowledge-based Systems

Citation: Jean Lieber: Strong, Fuzzy and Smooth Hierarchical Classification for Case-Based Problem Solving . In F. van Harmelen (ed.): ECAI2002, Proceedings of the 15th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2002, pp.81-85.


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ECAI-2002 is organised by the European Coordinating Committee for Artificial Intelligence (ECCAI) and hosted by the UniversitÚ Claude Bernard and INSA, Lyon, on behalf of Association Franšaise pour l'Intelligence Artificielle.