%0 Journal Article %1 Kleer1987 %A de Kleer, Johan %A Williams, Brian C. %D 1987 %J Artificial Intelligence %K AI GDE artificial diagnostic engine general intelligence %N 1 %P 97--130 %T Diagnosing multiple faults %V 32 %X Diagnostic tasks require determining the di®er- ences between a model of an artifact and the ar- tifact itself. The di®erences between the mani- fested behavior of the artifact and the predicted behavior of the model guide the search for the di®erences between the artifact and its model. The diagnostic procedure presented in this pa- per is model-based, inferring the behavior of the composite device from knowledge of the structure and function of the individual compo- nents comprising the device. The system (GDE | General Diagnostic Engine) has been imple- mented and tested on many examples in the domain of troubleshooting digital circuits. This research makes several novel contribu- tions: First, the system diagnoses failures due to multiple faults. Second, failure candidates are represented and manipulated in terms of minimal sets of violated assumptions, resulting in an e±cient diagnostic procedure. Third, the diagnostic procedure is incremental, exploit- ing the iterative nature of diagnosis. Fourth, a clear separation is drawn between diagnosis and behavior prediction, resulting in a domain (and inference procedure) independent diag- nostic procedure. Fifth, GDE combines model- based prediction with sequential diagnosis to propose measurements to localize the faults. The normally required conditional probabilities are computed from the structure of the device and models of its components. This capabil- ity results from a novel way of incorporating probabilities and information theory into the context mechanism provided by Assumption- Based Truth Maintenance.

@article{Kleer1987, abstract = {Diagnostic tasks require determining the di®er- ences between a model of an artifact and the ar- tifact itself. The di®erences between the mani- fested behavior of the artifact and the predicted behavior of the model guide the search for the di®erences between the artifact and its model. The diagnostic procedure presented in this pa- per is model-based, inferring the behavior of the composite device from knowledge of the structure and function of the individual compo- nents comprising the device. The system (GDE | General Diagnostic Engine) has been imple- mented and tested on many examples in the domain of troubleshooting digital circuits. This research makes several novel contribu- tions: First, the system diagnoses failures due to multiple faults. Second, failure candidates are represented and manipulated in terms of minimal sets of violated assumptions, resulting in an e±cient diagnostic procedure. Third, the diagnostic procedure is incremental, exploit- ing the iterative nature of diagnosis. Fourth, a clear separation is drawn between diagnosis and behavior prediction, resulting in a domain (and inference procedure) independent diag- nostic procedure. Fifth, GDE combines model- based prediction with sequential diagnosis to propose measurements to localize the faults. The normally required conditional probabilities are computed from the structure of the device and models of its components. This capabil- ity results from a novel way of incorporating probabilities and information theory into the context mechanism provided by Assumption- Based Truth Maintenance.}, added-at = {2009-07-20T21:42:01.000+0200}, author = {de Kleer, Johan and Williams, Brian C.}, biburl = {https://www.bibsonomy.org/bibtex/2c86415cfed16ecb5761e730ca8f86c90/mandel}, citeulike-article-id = {3508842}, interhash = {2084890048bf3345349dda5c3fbc13d3}, intrahash = {c86415cfed16ecb5761e730ca8f86c90}, journal = {Artificial Intelligence}, keywords = {AI GDE artificial diagnostic engine general intelligence}, number = 1, pages = {97--130}, posted-at = {2008-11-13 14:13:58}, priority = {2}, timestamp = {2009-07-20T21:43:38.000+0200}, title = {Diagnosing multiple faults}, volume = 32, year = 1987 }