Uncertainty in Artificial Intelligence
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Deterministic POMDPs Revisited
Blai Bonet
We study a subclass of POMDPs, called Deterministic POMDPs, that is characterized by deterministic actions and observations. These models do not provide the same generality of POMDPs yet they capture a number of interesting and challenging problems, and permit more efficient algorithms. Indeed, some of the recent work in planning is built around such assumptions mainly by the quest of amenable models more expressive than the classical deterministic models. We provide results about the fundamental properties of Deterministic POMDPs, their relation with AND/OR search problems and algorithms, and their computational complexity.
Keywords: null
Pages: 59-66
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PDF Link: /papers/09/p59-bonet.pdf
AUTHOR = "Blai Bonet ",
TITLE = "Deterministic POMDPs Revisited",
BOOKTITLE = "Proceedings of the Twenty-Fifth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-09)",
ADDRESS = "Corvallis, Oregon",
YEAR = "2009",
PAGES = "59--66"

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