On combinatorial actions and CMABs with linear side information

Alexander Shleyfman, Antonín Komenda, Carmel Domshlak

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

25 Scopus citations

Abstract

Online planning algorithms are typically a tool of choice for dealing with sequential decision problems in combinatorial search spaces. Many such problems, however, also exhibit combinatorial actions, yet standard planning algorithms do not cope well with this type of 'the curse of dimensionality'. Following a recently opened line of related work on combinatorial multi-armed bandit (CMAB) problems, we propose a novel CMAB planning scheme, as well as two specific instances of this scheme, dedicated to exploiting what is called linear side information. Using a representative strategy game as a benchmark, we show that the resulting algorithms very favorably compete with the state-of-the-art.

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 BV
Pages825-830
Number of pages6
ISBN (Electronic)9781614994183
DOIs
StatePublished - 2014
Externally publishedYes
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
Volume263
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314

Conference

Conference21st European Conference on Artificial Intelligence, ECAI 2014
Country/TerritoryCzech Republic
CityPrague
Period18/08/1422/08/14

Bibliographical note

Publisher Copyright:
© 2014 The Authors and IOS Press.

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