Distribution over Beliefs for Memory Bounded Dec-POMDP Planning
Artificial Intelligence
2012-03-19 v1
Abstract
We propose a new point-based method for approximate planning in Dec-POMDP which outperforms the state-of-the-art approaches in terms of solution quality. It uses a heuristic estimation of the prior probability of beliefs to choose a bounded number of policy trees: this choice is formulated as a combinatorial optimisation problem minimising the error induced by pruning.
Cite
@article{arxiv.1203.3474,
title = {Distribution over Beliefs for Memory Bounded Dec-POMDP Planning},
author = {Gabriel Corona and Francois Charpillet},
journal= {arXiv preprint arXiv:1203.3474},
year = {2012}
}
Comments
Appears in Proceedings of the Twenty-Sixth Conference on Uncertainty in Artificial Intelligence (UAI2010)