Uncertainty in Artificial Intelligence
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An Application of Non-Monotonic Probabilistic Reasoning to Air Force Threat Correlation
Kathryn Laskey, Marvin Cohen
Abstract:
Current approaches to expert systems' reasoning under uncertainty fail to capture the iterative revision process characteristic of intelligent human reasoning. This paper reports on a system, called the Non-monotonic Probabilist, or NMP (Cohen, et al., 1985). When its inferences result in substantial conflict, NMP examines and revises the assumptions underlying the inferences until conflict is reduced to acceptable levels. NMP has been implemented in a demonstration computer-based system, described below, which supports threat correlation and in-flight route replanning by Air Force pilots.
Keywords:
Pages: 159-166
PS Link:
PDF Link: /papers/86/p159-laskey.pdf
BibTex:
@INPROCEEDINGS{Laskey86,
AUTHOR = "Kathryn Laskey and Marvin Cohen",
TITLE = "An Application of Non-Monotonic Probabilistic Reasoning to Air Force Threat Correlation",
BOOKTITLE = "Proceedings of the Second Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-86)",
PUBLISHER = "AUAI Press",
ADDRESS = "Corvallis, Oregon",
YEAR = "1986",
PAGES = "159--166"
}


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