On the properties of belief tracking for online contingent planning using regression

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

4 Scopus citations


Planning under partial observability typically requires some representation of the agent's belief state-either online to determine which actions are valid, or offline for planning. Due to its potential exponential size, efficient maintenance of a belief state is, thus, a key research challenge in this area. The state-of-the-art factored belief tracking (FBT) method addresses this problem by maintaining multiple smaller projected belief states, each involving only a subset of the variable set. Its complexity is exponential in the size of these subsets, as opposed to the entire variable set, without jeopardizing completeness. In this paper we develop the theory of regression to serve as an alternative tool for belief-state maintenance. Regression is a well known technique enjoying similar, and potentially even better worst-case complexity, as its complexity depends on the actions and observations that actually took place, rather than all actions and potential observations, as in the FBT method. On the other hand, FBT is likely to have better amortized complexity if the number of queries to the belief state is very large. An empirical comparison of regression with FBT-based belief maintenance is carried out, showing that the two perform similarly.

Original languageEnglish
Title of host publicationECAI 2014 - 21st European Conference on Artificial Intelligence, Including Prestigious Applications of Intelligent Systems, PAIS 2014, Proceedings
EditorsTorsten Schaub, Gerhard Friedrich, Barry O'Sullivan
PublisherIOS Press
Number of pages6
ISBN (Electronic)9781614994183
StatePublished - 1 Jan 2014
Event21st European Conference on Artificial Intelligence, ECAI 2014 - Prague, Czech Republic
Duration: 18 Aug 201422 Aug 2014

Publication series

NameFrontiers in Artificial Intelligence and Applications
ISSN (Print)0922-6389


Conference21st European Conference on Artificial Intelligence, ECAI 2014
Country/TerritoryCzech Republic


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