Uncertainty in Artificial Intelligence
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Solving Asymmetric Decision Problems with Influence Diagrams
Runping Qi, Nevin Zhang, David Poole
Abstract:
While influence diagrams have many advantages as a representation framework for Bayesian decision problems, they have a serious drawback in handling asymmetric decision problems. To be represented in an influence diagram, an asymmetric decision problem must be symmetrized. A considerable amount of unnecessary computation may be involved when a symmetrized influence diagram is evaluated by conventional algorithms. In this paper we present an approach for avoiding such unnecessary computation in influence diagram evaluation.
Keywords:
Pages: 491-497
PS Link:
PDF Link: /papers/94/p491-qi.pdf
BibTex:
@INPROCEEDINGS{Qi94,
AUTHOR = "Runping Qi and Nevin Zhang and David Poole",
TITLE = "Solving Asymmetric Decision Problems with Influence Diagrams",
BOOKTITLE = "Proceedings of the Tenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-94)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1994",
PAGES = "491--497"
}


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