Uncertainty in Artificial Intelligence
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Approximate Planning for Factored POMDPs using Belief State Simplification
David McAllester, Satinder Singh
Abstract:
We are interested in the problem of planning for factored POMDPs. Building on the recent results of Kearns, Mansour and Ng, we provide a planning algorithm for factored POMDPs that exploits the accuracy-efficiency tradeoff in the belief state simplification introduced by Boyen and Koller.
Keywords: POMDPs, Belief State Planning, Factored POMDPs
Pages: 409-416
PS Link: http://www.research.att.com/~baveja/Papers/DaveSinghUAI99.ps.gz
PDF Link: /papers/99/p409-mcallester.pdf
BibTex:
@INPROCEEDINGS{McAllester99,
AUTHOR = "David McAllester and Satinder Singh",
TITLE = "Approximate Planning for Factored POMDPs using Belief State Simplification",
BOOKTITLE = "Proceedings of the Fifteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-99)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1999",
PAGES = "409--416"
}


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