Approximate Planning for Factored POMDPs using Belief State Simplification
Artificial Intelligence
2013-01-30 v1
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.
Cite
@article{arxiv.1301.6719,
title = {Approximate Planning for Factored POMDPs using Belief State Simplification},
author = {David A. McAllester and Satinder Singh},
journal= {arXiv preprint arXiv:1301.6719},
year = {2013}
}
Comments
Appears in Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI1999)