Uncertainty in Artificial Intelligence
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Practical Issues in Constructing a Bayes' Belief Network
Max Henrion
Abstract:
Bayes belief networks and influence diagrams are tools for constructing coherent probabilistic representations of uncertain knowledge. The process of constructing such a network to represent an expert's knowledge is used to illustrate a variety of techniques which can facilitate the process of structuring and quantifying uncertain relationships. These include some generalizations of the "noisy OR gate" concept. Sensitivity analysis of generic elements of Bayes' networks provides insight into when rough probability assessments are sufficient and when greater precision may be important.
Keywords: Belief Networks, Influence Diagrams, Bayesian Networks
Pages: 132-139
PS Link:
PDF Link: /papers/87/p132-henrion.pdf
BibTex:
@INPROCEEDINGS{Henrion87,
AUTHOR = "Max Henrion ",
TITLE = "Practical Issues in Constructing a Bayes' Belief Network",
BOOKTITLE = "Proceedings of the Third Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-87)",
PUBLISHER = "AUAI Press",
ADDRESS = "Corvallis, Oregon",
YEAR = "1987",
PAGES = "132--139"
}


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