AAAI Publications, Twenty-First International Joint Conference on Artificial Intelligence

Font Size: 
Topological Order Planner for POMDPs
Jilles Steeve Dibangoye, Guy Shani, Brahim Chaib-draa, Abdell-Illah Mouaddib

Last modified: 2009-06-26

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.

Full Text: PDF