Topological Order Planner for POMDPs
Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence. Pages 1684-1688.
Abstract
Over the past few years, point-based POMDP solvers scaled up to produce approximate solutions to mid-sized domains. However, to solve real world problems, solvers must exploit the structure of the domain. In this paper we focus on the topological structure of the problem, where the state space contains layers of states. We present here the Topological Order Planner (TOP) that utilizes the topological structure of the domain to compute belief space trajectories. TOP rapidly produces trajectories focused on the solveable regions of the belief space, thus reducing the number of redundant backups considerably. We demonstrate TOP to produce good quality policies faster than any other point-based algorithm on domains with sufficient structure.Jilles Steeve Dibangoye, Guy Shani, Brahim Chaib-draa, Abdell-Illah Mouaddib
@inproceedings{ijcai2009p281,
title = {Topological Order Planner for POMDPs},
author = {Dibangoye, Jilles Steeve and Shani, Guy and Chaib-draa, Brahim and Mouaddib, Abdel-Illah},
booktitle = {Proceedings of the Twenty-First International Joint Conference on
Artificial Intelligence, {IJCAI-09}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Hiroaki Kitano},
pages = {1684--1688},
year = {2009},
url = {https://ijcai.org/proceedings/2009/281},
}
TY - CPAPER TI - Topological Order Planner for POMDPs AU - Dibangoye, Jilles Steeve AU - Shani, Guy AU - Chaib-draa, Brahim AU - Mouaddib, Abdel-Illah T2 - Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence, IJCAI-09 PB - International Joint Conferences on Artificial Intelligence PY - 2009 SP - 1684 EP - 1688 UR - https://ijcai.org/proceedings/2009/281 ER -Copied
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