Uncertainty in Artificial Intelligence
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Three Arguments for Extending the Framework of Probability
John Fox
Abstract:
The last few years has seen a growing debate about techniques for managing uncertainty in AI systems. Unfortunately this debate has been cast as a rivalry between AI methods and classical probability based ones. Three arguments for extending the probability framework of uncertainty are presented, none of which imply a challenge to classical methods. These are (1) explicit representation of several types of uncertainty, specifically possibility and plausibility, as well as probability, (2) the use of weak methods for uncertainty management in problems which are poorly defined, and (3) symbolic representation of different uncertainty calculi and methods for choosing between them.
Keywords: Managing Uncertainty, Framework of Probability
Pages: 447-458
PS Link:
PDF Link: /papers/85/p447-fox.pdf
BibTex:
@INPROCEEDINGS{Fox85,
AUTHOR = "John Fox ",
TITLE = "Three Arguments for Extending the Framework of Probability",
BOOKTITLE = "Uncertainty in Artificial Intelligence Annual Conference on Uncertainty in Artificial Intelligence (UAI-85)",
PUBLISHER = "Elsevier Science",
ADDRESS = "Amsterdam, NL",
YEAR = "1985",
PAGES = "447--458"
}


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