---
title: "Using core beliefs for point-based value iteration"
authors:
  - "Masoumeh T. Izadi"
  - "Ajit V. Rajwade"
  - "Doina Precup"
doi: ""
url: "https://ijcai.org/proceedings/2005/310"
pdf: "https://ijcai.org/proceedings/2005/0310.pdf"
venue: "Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence"
year: 2005
pages: "1751-1752"
track: ""
keywords:
---

# Using core beliefs for point-based value iteration

Masoumeh T. Izadi, Ajit V. Rajwade, Doina Precup

*Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence*, pages 1751-1752.

## Abstract

Recent research on point-based approximation algorithms for POMDPs demonstrated that good solutions to POMDP problems can be obtained without considering the entire belief simplex. For instance, the Point Based Value Iteration (PBVI) algorithm [Pineau et al., 2003] computes the value function only for a small set of belief states and iteratively adds more points to the set as needed. A key component of the algorithm is the strategy for selecting belief points, such that the space of reachable beliefs is well covered. This paper presents a new method for selecting an initial set of representative belief points, which relies on finding first the basis for the reachable belief simplex. Our approach has better worst-case performance than the original PBVI heuristic, and performs well in several standard POMDP tasks.