Uncertainty in Artificial Intelligence
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Using Potential Influence Diagrams for Probabilistic Inference and Decision Making
Ross Shachter, Pierre Ndilikilikesha
Abstract:
The potential influence diagram is a generalization of the standard "conditional" influence diagram, a directed network representation for probabilistic inference and decision analysis [Ndilikilikesha, 1991]. It allows efficient inference calculations corresponding exactly to those on undirected graphs. In this paper, we explore the relationship between potential and conditional influence diagrams and provide insight into the properties of the potential influence diagram. In particular, we show how to convert a potential influence diagram into a conditional influence diagram, and how to view the potential influence diagram operations in terms of the conditional influence diagram.
Keywords:
Pages: 383-390
PS Link:
PDF Link: /papers/93/p383-shachter.pdf
BibTex:
@INPROCEEDINGS{Shachter93,
AUTHOR = "Ross Shachter and Pierre Ndilikilikesha",
TITLE = "Using Potential Influence Diagrams for Probabilistic Inference and Decision Making",
BOOKTITLE = "Proceedings of the Ninth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-93)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1993",
PAGES = "383--390"
}


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