Uncertainty in Artificial Intelligence
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Knowledge Integration for Conditional Probability Assessments
Angelo Gilio, Fulvio Spezzaferri
In the probabilistic approach to uncertainty management the input knowledge is usually represented by means of some probability distributions. In this paper we assume that the input knowledge is given by two discrete conditional probability distributions, represented by two stochastic matrices P and Q. The consistency of the knowledge base is analyzed. Coherence conditions and explicit formulas for the extension to marginal distributions are obtained in some special cases.
Pages: 98-103
PS Link:
PDF Link: /papers/92/p98-gilio.pdf
AUTHOR = "Angelo Gilio and Fulvio Spezzaferri",
TITLE = "Knowledge Integration for Conditional Probability Assessments",
BOOKTITLE = "Proceedings of the Eighth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-92)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Mateo, CA",
YEAR = "1992",
PAGES = "98--103"

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