Efficient deterministic approximation algorithms for non-myopic value of information in graphical models

Yan Radovilsky, Guy Shattah, Solomon Eyal Shimony

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

6 Scopus citations

Abstract

Agents operating in the real world need to handle both uncertainty and resource constraints. Typical problems in this domain are optimization of sequences of observations, and optimal allocation of computation tasks during reasoning and search (also known as meta-reasoning). In both domains, a crucial issue is value of information, a quantity hard to compute in general, and thus usually estimated using severe assumptions, such as myopic and independence of information sources. This paper extends recent work on non-myopic value of information in graphical models, that assumed a chain-shaped graph and exact measurements. Suitably relaxing the assumption of exact measurements still allows for a provably close approximation of the optimal subset (of observations) selection, and for approximating the optimal conditional plan. The method is shown to be efficient and to provide a significant advantage in expected reward over the myopic and greedy value of information scheme.

Original languageEnglish
Title of host publication2006 IEEE International Conference on Systems, Man and Cybernetics
PublisherInstitute of Electrical and Electronics Engineers
Pages2559-2564
Number of pages6
ISBN (Print)1424401003, 9781424401000
DOIs
StatePublished - 1 Jan 2006
Event2006 IEEE International Conference on Systems, Man and Cybernetics - Taipei, Taiwan, Province of China
Duration: 8 Oct 200611 Oct 2006

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume3
ISSN (Print)1062-922X

Conference

Conference2006 IEEE International Conference on Systems, Man and Cybernetics
Country/TerritoryTaiwan, Province of China
CityTaipei
Period8/10/0611/10/06

ASJC Scopus subject areas

  • General Engineering

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