Fast Value Iteration for Goal-Directed Markov Decision Processes
Abstract
Planning problems where effects of actions are non-deterministic can be modeled as Markov decision processes. Planning problems axe usually goal-directed. This paper proposes several techniques for exploiting the goal-directedness to accelerate value iteration, a standard algorithm for solving Markov decision processes. Empirical studies have shown that the techniques can bring about significant speedups.
Cite
Text
Zhang and Zhang. "Fast Value Iteration for Goal-Directed Markov Decision Processes." Conference on Uncertainty in Artificial Intelligence, 1997.Markdown
[Zhang and Zhang. "Fast Value Iteration for Goal-Directed Markov Decision Processes." Conference on Uncertainty in Artificial Intelligence, 1997.](https://mlanthology.org/uai/1997/zhang1997uai-fast/)BibTeX
@inproceedings{zhang1997uai-fast,
title = {{Fast Value Iteration for Goal-Directed Markov Decision Processes}},
author = {Zhang, Nevin Lianwen and Zhang, Weihong},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {1997},
pages = {489-494},
url = {https://mlanthology.org/uai/1997/zhang1997uai-fast/}
}