Uncertainty in Artificial Intelligence
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An Anytime Algorithm for Decision Making under Uncertainty
Michael Horsch, David Poole
Abstract:
We present an anytime algorithm which computes policies for decision problems represented as multi-stage influence diagrams. Our algorithm constructs policies incrementally, starting from a policy which makes no use of the available information. The incremental process constructs policies which includes more of the information available to the decision maker at each step. While the process converges to the optimal policy, our approach is designed for situations in which computing the optimal policy is infeasible. We provide examples of the process on several large decision problems, showing that, for these examples, the process constructs valuable (but sub-optimal) policies before the optimal policy would be available by traditional methods.
Keywords:
Pages: 246-255
PS Link: ftp://ftp.cs.ubc.ca/ftp/local/poole/papers/randaccref.ps.gz
PDF Link: /papers/98/p246-horsch.pdf
BibTex:
@INPROCEEDINGS{Horsch98,
AUTHOR = "Michael Horsch and David Poole",
TITLE = "An Anytime Algorithm for Decision Making under Uncertainty",
BOOKTITLE = "Proceedings of the Fourteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-98)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1998",
PAGES = "246--255"
}


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