DocumentCode :
3338196
Title :
Higher-level causal reasoning for diagnosis
Author :
Schaefer, Philip
Author_Institution :
Martin Marietta Astronaut. Group, Denver, CO, USA
fYear :
1988
fDate :
25-27 May 1988
Firstpage :
33
Lastpage :
38
Abstract :
The author presents a higher-level technique for causal reasoning and diagnosis. Modules are the basic components in the resulting representation. Considerations unique to causal reasoning at a high level are discussed, and an algorithm and examples incorporating the resulting characteristics are presented. Using higher-level causal reasoning has been shown to be a useful technique for introducing the flexibility of causal reasoning to complex systems for which module-level diagnosis is desired. A prototype system, FEXPR, has been successfully implemented to demonstrate the higher-level causal diagnosis approach
Keywords :
artificial intelligence; knowledge engineering; FEXPR; algorithm; complex systems; flexibility; higher-level causal diagnosis; higher-level causal reasoning; module-level diagnosis; prototype system; Artificial intelligence; Association rules; Automation; Circuit faults; Diagnostic expert systems; Fault diagnosis; Intelligent systems; Predictive models; Robustness; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence for Industrial Applications, 1988. IEEE AI '88., Proceedings of the International Workshop on
Conference_Location :
Hitachi City
Type :
conf
DOI :
10.1109/AIIA.1988.13266
Filename :
13266
Link To Document :
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