Scaling Up: Solving POMDPs through Value Based Clustering

Yan Virin, Guy Shani, Shimony Eyal, Brafman Ronen

We present here a point-based value iteration algorithm for solving POMDPs, that orders belief state backups smartly based on a clustering of the underlying MDP states. We show our SCVI algorithm to converge faster than state of the art point-based algorithms.

Subjects: 3. Automated Reasoning; 3.4 Probabilistic Reasoning

Submitted: Apr 10, 2007


This page is copyrighted by AAAI. All rights reserved. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.