Diagnostic reasoning based on structure and behavior
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
The use of design descriptions in automated diagnosis
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence
Readings in nonmonotonic reasoning
A theory of diagnosis from first principles
Readings in nonmonotonic reasoning
Readings in nonmonotonic reasoning
Model-based reasoning: troubleshooting
Exploring artificial intelligence
"Physical negation": integrating fault models into the general diagnostic engine
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Diagnosis with behavioral modes
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
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A faulty component that behaves consistently over time is said to behave non-intermittently. For any given set of inputs, such a component will always generate the same output. Assuming that components fail non-intermittently is a common simplifying strategy used by diagnosticians, because (1) many real-world devices often fail this way, (2) this strategy removes the need to repeat experiments, and (3) this strategy allows information from independent examples of system behavior to be combined in relatively simple ways. This paper extends the formal framework for diagnosis developed in [7, 12] to allow nonintermittency assumptions. In addition we show how the definitions can be easily integrated into ATMS-based diagnosis engines. Within our formulation, components can be individually assumed to be intermittent or nonintermittent.