A qualitative physics based on confluences
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
A Qualitative Modeling Shell for Process Diagnosis
IEEE Software
Causal understanding of patient illness in medical diagnosis
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
CSEL: a language for expert systems for diagnosis
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1
From application shell to knowledge acquisition system
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 1
Repair strategies in a diagnostic expert system
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 1
Model-based fault diagnosis: knowledge acquisition and system design
IEA/AIE '89 Proceedings of the 2nd international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 1
Cell assemblies for diagnostic problem-solving
Neurocomputing
Paper: Graphical knowledge acquisition for medical diagnostic expert systems
Artificial Intelligence in Medicine
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TEST (Troubleshooting Expert System Tool) is an application shell that provides a domain-independent diagnostic problem solver together with a library of schematic prototypes. TEST fills a design niche halfway between rule-based and causal-model approaches. This approach has resulted in a design that meets several functional requirements for an effective troubleshooting shelt. Most critically, TEST can represent both the impact of failure-modes on a machine or system of interest, as well as the heuristic problem-solving behavior which can lead to rapid conclusions. This paper provides an overview of TEST's approach to diagnosis. As a special purpose application shell, TEST provides considerably more leverage to developers than can be gained through the use of general purpose heuristic classification systems.