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Abstract

This paper introduces the Point-Based Value Iteration (PBVI) algorithm for POMDP planning. PBVI approximates an exact value iteration solution by selecting a small set of representative belief points and then tracking the value and its derivative for those points only. By using stochastic trajectories to choose belief points, and by maintaining only one value hyper-plane per point, PBVI successfully solves large problems: we present results on a robotic laser tag problem as well as three test domains from the literature.

Notes

Associated Lab(s) / Group(s): Robot Learning Lab

Number of pages: 8

Text Reference

Joelle Pineau, Geoffrey Gordon, and Sebastian Thrun, "Point-based value iteration: An anytime algorithm for POMDPs," International Joint Conference on Artificial Intelligence (IJCAI), August, 2003, pp. 1025 - 1032.

BibTeX Reference

@inproceedings{Pineau_2003_4826,
   author = "Joelle Pineau and Geoffrey Gordon and Sebastian Thrun",
   title = "Point-based value iteration: An anytime algorithm for POMDPs",
   booktitle = "International Joint Conference on Artificial Intelligence (IJCAI)",
   pages = "1025 - 1032",
   month = "August",
   year = "2003",
}

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