Uncertainty in Artificial Intelligence
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Management of Uncertainty in the Multi-Level Monitoring and Diagnosis of the Time of Flight Scintillation Array
Robert Paasch, Alice Agogino
Abstract:
We present a general architecture for the monitoring and diagnosis of large scale sensor-based systems with real time diagnostic constraints. This architecture is multileveled, combining a single monitoring level based on statistical methods with two model based diagnostic levels. At each level, sources of uncertainty are identified, and integrated methodologies for uncertainty management are developed. The general architecture was applied to the monitoring and diagnosis of a specific nuclear physics detector at Lawrence Berkeley National Laboratory that contained approximately 5000 components and produced over 500 channels of output data. The general architecture is scalable, and work is ongoing to apply it to detector systems one and two orders of magnitude more complex.
Keywords:
Pages: 257-263
PS Link:
PDF Link: /papers/91/p257-paasch.pdf
BibTex:
@INPROCEEDINGS{Paasch91,
AUTHOR = "Robert Paasch and Alice Agogino",
TITLE = "Management of Uncertainty in the Multi-Level Monitoring and Diagnosis of the Time of Flight Scintillation Array",
BOOKTITLE = "Proceedings of the Seventh Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-91)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Mateo, CA",
YEAR = "1991",
PAGES = "257--263"
}


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