Uncertainty in Artificial Intelligence
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Exact Reasoning About Uncertainty : On the Design of Expert Systems for Decision Support
Samuel Holtzman, John Breese
Abstract:
This paper focuses on designing expert systems to support decision making in complex, uncertain environments. In this context, our research indicates that strictly probabilistic representations, which enable the use of decision-theoretic reasoning, are highly preferable to recently proposed alternatives (e.g., fuzzy set theory and Dempster-Shafer theory). Furthermore, we discuss the language of influence diagrams and a corresponding methodology -decision analysis -- that allows decision theory to be used effectively and efficiently as a decision-making aid. Finally, we use RACHEL, a system that helps infertile couples select medical treatments, to illustrate the methodology of decision analysis as basis for expert decision systems.
Keywords: Expert Systems, Influence Diagrams
Pages: 339-345
PS Link:
PDF Link: /papers/85/p339-holtzman.pdf
BibTex:
@INPROCEEDINGS{Holtzman85,
AUTHOR = "Samuel Holtzman and John Breese",
TITLE = "Exact Reasoning About Uncertainty : On the Design of Expert Systems for Decision Support",
BOOKTITLE = "Uncertainty in Artificial Intelligence Annual Conference on Uncertainty in Artificial Intelligence (UAI-85)",
PUBLISHER = "Elsevier Science",
ADDRESS = "Amsterdam, NL",
YEAR = "1985",
PAGES = "339--345"
}


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