Efficient ADD operations for point-based algorithms

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

28 Scopus citations

Abstract

During the past few years, point-based POMDP solvers have gradually scaled up to handle medium sized domains through better selection of the set of points and efficient backup methods. Point-based research has focused on flat, explicit representation of the state space, yet in many realistic domains a factored representation is more appropriate. The latter have exponentially large state-spaces, and current methods are unlikely to handle models of reasonable size. Thus, adapting point-based methods to factored representations by modeling prepositional state spaces better, e.g. by using Algebraic Decision Diagrams (ADDs) is needed. While a straightforward ADD-based implementation can effectively tackle large factored POMDPs, we propose several techniques to further improve scalability. In particular, we show how ADDs can be used successfully in factored domains that exhibit reasonable locality. Our algorithms are several orders of magnitude faster than current point-based algorithms used with flat representations.

Original languageEnglish
Title of host publicationICAPS 2008 - Proceedings of the 18th International Conference on Automated Planning and Scheduling
Pages330-337
Number of pages8
StatePublished - 1 Dec 2008
Event18th International Conference on Automated Planning and Scheduling, ICAPS 2008 - Sydney, NSW, Australia
Duration: 14 Sep 200818 Sep 2008

Publication series

NameICAPS 2008 - Proceedings of the 18th International Conference on Automated Planning and Scheduling

Conference

Conference18th International Conference on Automated Planning and Scheduling, ICAPS 2008
Country/TerritoryAustralia
CitySydney, NSW
Period14/09/0818/09/08

ASJC Scopus subject areas

  • Strategy and Management
  • Artificial Intelligence
  • Computer Science Applications

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