ML Anthology

Approximate Planning for Factored POMDPs Using Belief State Simplification

David A. McAllester, Satinder Singh
UAI 1999 pp. 409-416
/uai/1999/mcallester1999uai-approximate/

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.

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Cite

Text

McAllester and Singh. "Approximate Planning for Factored POMDPs Using Belief State Simplification." Conference on Uncertainty in Artificial Intelligence, 1999.

Markdown

[McAllester and Singh. "Approximate Planning for Factored POMDPs Using Belief State Simplification." Conference on Uncertainty in Artificial Intelligence, 1999.](https://mlanthology.org/uai/1999/mcallester1999uai-approximate/)

BibTeX

@inproceedings{mcallester1999uai-approximate,
  title     = {{Approximate Planning for Factored POMDPs Using Belief State Simplification}},
  author    = {McAllester, David A. and Singh, Satinder},
  booktitle = {Conference on Uncertainty in Artificial Intelligence},
  year      = {1999},
  pages     = {409-416},
  url       = {https://mlanthology.org/uai/1999/mcallester1999uai-approximate/}
}