{"type":"ScholarlyArticle","title":"Using core beliefs for point-based value iteration","authors":[{"name":"Masoumeh T. Izadi","slug":"masoumeh-t-izadi","given":"Masoumeh T.","family":"Izadi","affiliation":""},{"name":"Ajit V. Rajwade","slug":"ajit-v-rajwade","given":"Ajit V.","family":"Rajwade","affiliation":""},{"name":"Doina Precup","slug":"doina-precup","given":"Doina","family":"Precup","affiliation":""}],"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.","doi":null,"url":"https://ijcai.org/proceedings/2005/310","pdf":"https://ijcai.org/proceedings/2005/0310.pdf","markdown":"https://ijcai.org/proceedings/2005/310.md","bibtex":"https://ijcai.org/proceedings/2005/bibtex/310","volume":{"slug":"2005","title":"Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2005","url":"https://ijcai.org/proceedings/2005/","year":2005,"location":"Edinburgh, Scotland, UK","dates":"","editors":"","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":310,"pages":{"first":1751,"last":1752},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}