FALLDATEN: Case-Based Reasoning for the Diagnosis of Technical Devices

This work may not be copied or reproduced in whole of part for any commercial purpose. Permission to copy in whole or part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of the Labor für Künstliche Intelligenz, Hamburg, Germany; an acknowledgement of the authors and individual contributors to the work; all applicable portions of this copyright notice. Copying, reproducing, or republishing for any other purpose shall require an agreement with Labor für Künstliche Intelligenz. Abstract We investigate the suitability of case-based reasoning supporting experts during technical diagnosis. Diagnosis is not considered as a classiication task, but as a process to be guided by computer assisted experience. This corresponds to a exible case completionn approach. Flexibility is also needed for the expert view with predominant interest in the unexpected, unpredictable cases. Integration of further knowledge sources (domain knowledge, common knowledge) is investigated in the project. Two diierent approaches based on semantic nets are investigated: Fallexperte-D makes use of Case Retrieval Nets (CRN) that are based on spreading activation techniques. Falldaten-DL employs description logics enhanced by concrete domains.