Forward search value iteration for POMDPs

Research output: Contribution to journalConference articlepeer-review

80 Scopus citations

Abstract

Recent scaling up of POMDP solvers towards realistic applications is largely due to point-based methods which quickly converge to an approximate solution formedium-sized problems. Of this family HSVI, which uses trial-based asynchronous value iteration, can handle the largest domains. In this paper we suggest a new algorithm, FSVI, that uses the underlying MDP to traverse the belief space towards rewards, finding sequences of useful back-ups, and show how it scales up better than HSVI on larger benchmarks.

Original languageEnglish
Pages (from-to)2619-2624
Number of pages6
JournalIJCAI International Joint Conference on Artificial Intelligence
StatePublished - 1 Dec 2007
Event20th International Joint Conference on Artificial Intelligence, IJCAI 2007 - Hyderabad, India
Duration: 6 Jan 200712 Jan 2007

ASJC Scopus subject areas

  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'Forward search value iteration for POMDPs'. Together they form a unique fingerprint.

Cite this