Uncertainty in Artificial Intelligence
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Heuristic Search Value Iteration for POMDPs
Trey Smith, Reid Simmons
Abstract:
We present a novel POMDP planning algorithm called heuristic search value iteration (HSVI).HSVI is an anytime algorithm that returns a policy and a provable bound on its regret with respect to the optimal policy. HSVI gets its power by combining two well-known techniques: attention-focusing search heuristics and piecewise linear convex representations of the value function. HSVI's soundness and convergence have been proven. On some benchmark problems from the literature, HSVI displays speedups of greater than 100 with respect to other state-of-the-art POMDP value iteration algorithms. We also apply HSVI to a new rover exploration problem 10 times larger than most POMDP problems in the literature.
Keywords:
Pages: 520-527
PS Link:
PDF Link: /papers/04/p520-smith.pdf
BibTex:
@INPROCEEDINGS{Smith04,
AUTHOR = "Trey Smith and Reid Simmons",
TITLE = "Heuristic Search Value Iteration for POMDPs",
BOOKTITLE = "Proceedings of the Twentieth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-04)",
PUBLISHER = "AUAI Press",
ADDRESS = "Arlington, Virginia",
YEAR = "2004",
PAGES = "520--527"
}


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