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Metric state space reinforcement learning for a vision-capable mobile robot

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dc.contributor.authorZhumatiy, Viktor
dc.contributor.authorGomez, Faustino
dc.contributor.authorHutter, Marcus
dc.contributor.authorSchmidhuber, Jürgen
dc.date.accessioned2015-12-08T22:27:22Z
dc.date.issued2006
dc.date.updated2016-02-24T11:43:26Z
dc.description.abstractWe address the problem of autonomously learning controllers for vision-capable mobile robots. We extend McCallum's (1995) Nearest-Sequence Memory algorithm to allow for general metrics over state-action trajectories. We demonstrate the feasibility of our
dc.identifier.isbn9781586035952
dc.identifier.urihttp://hdl.handle.net/1885/34046
dc.publisherIOS Press
dc.relation.ispartofIntelligent Autonomous Systems 9: proceedings of the 9th international conference on intelligent autonomous systems, Tokyo 2006
dc.relation.isversionof1st Edition
dc.rightsCopyright Information: © 2006 The Author(s).
dc.subjectKeywords: Computer models; Discretizations; Learning controllers; Partial observability; Piecewise-continuous; Sensor inputs; State space; Algorithms; Reinforcement learning; Mobile robots Mobile robots; Reinforcement learning
dc.titleMetric state space reinforcement learning for a vision-capable mobile robot
dc.typeBook chapter
local.bibliographicCitation.lastpage281
local.bibliographicCitation.placeofpublicationAmsterdam, The Netherlands
local.bibliographicCitation.startpage272
local.contributor.affiliationZhumatiy, Viktor, IDSIA-Istituto Dalle Molle di Studi sull Intelligenza Artificiale
local.contributor.affiliationGomez, Faustino, IDSIA-Istituto Dalle Molle di Studi sull Intelligenza Artificiale
local.contributor.affiliationHutter, Marcus, College of Engineering and Computer Science, ANU
local.contributor.affiliationSchmidhuber, Jurgen, IDSIA-Istituto Dalle Molle di Studi sull Intelligenza Artificiale
local.contributor.authoruidHutter, Marcus, u4350841
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.identifier.absfor080401 - Coding and Information Theory
local.identifier.absfor010405 - Statistical Theory
local.identifier.absfor080199 - Artificial Intelligence and Image Processing not elsewhere classified
local.identifier.ariespublicationu8803936xPUB108
local.identifier.scopusID2-s2.0-84871868155
local.type.statusPublished Version

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