ML Anthology

An Improved Grid-Based Approximation Algorithm for POMDPs

Rong Zhou, Eric A. Hansen
IJCAI 2001 pp. 707-716
/ijcai/2001/zhou2001ijcai-improved/

Abstract

Although a partially observable Markov decision process (POMDP) provides an appealing model for problems of planning under uncertainty, exact algorithms for POMDPs are intractable. This motivates work on approximation algorithms, and grid-based approximation is a widely-used approach. We describe a novel approach to grid-based approximation that uses a variable-resolution regular grid, and show that it outperforms previous grid-based approaches to approximation. 1

Semantic Scholar

Cite

Text

Zhou and Hansen. "An Improved Grid-Based Approximation Algorithm for POMDPs." International Joint Conference on Artificial Intelligence, 2001.

Markdown

[Zhou and Hansen. "An Improved Grid-Based Approximation Algorithm for POMDPs." International Joint Conference on Artificial Intelligence, 2001.](https://mlanthology.org/ijcai/2001/zhou2001ijcai-improved/)

BibTeX

@inproceedings{zhou2001ijcai-improved,
  title     = {{An Improved Grid-Based Approximation Algorithm for POMDPs}},
  author    = {Zhou, Rong and Hansen, Eric A.},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2001},
  pages     = {707-716},
  url       = {https://mlanthology.org/ijcai/2001/zhou2001ijcai-improved/}
}