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Self-optimizing and Pareto-optimal policies in general environments based on Bayes-mixtures

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dc.contributor.authorHutter, Marcus
dc.date.accessioned2015-09-02T05:19:54Z
dc.date.available2015-09-02T05:19:54Z
dc.date.issued2002
dc.identifier.isbn978-3-540-43836-6en_AU
dc.identifier.issn0302-9743en_AU
dc.identifier.urihttp://hdl.handle.net/1885/15096
dc.publisherSpringer Verlagen_AU
dc.relation.ispartofComputational Learning Theory: 15th Annual Conference on Computational Learning Theory, COLT 2002 Sydney, Australia, July 8–10, 2002 Proceedingsen_AU
dc.rights© Springer-Verlag Berlin Heidelberg 2002. http://www.sherpa.ac.uk/romeo/issn/0302-9743/..."Author's post-print on any open access repository after 12 months after publication" from SHERPA/RoMEO site (as at 2/09/15)en_AU
dc.subjectRational agentsen_AU
dc.subjectsequential decision theoryen_AU
dc.subjectreinforcement learningen_AU
dc.subjectvalue functionen_AU
dc.subjectBayes mixturesen_AU
dc.subjectself-optimizing policiesen_AU
dc.subjectPareto-optimalityen_AU
dc.subjectunbounded effective horizonen_AU
dc.subject(non) Markov decision processesen_AU
dc.titleSelf-optimizing and Pareto-optimal policies in general environments based on Bayes-mixturesen_AU
dc.typeConference paperen_AU
dcterms.accessRightsOpen Access
local.bibliographicCitation.lastpage379en_AU
local.bibliographicCitation.startpage364en_AU
local.contributor.affiliationHutter, M., Research School of Computer Science, The Australian National Universityen_AU
local.contributor.authoruidu4350841en_AU
local.identifier.citationvolume2375en_AU
local.identifier.doi10.1007/3-540-45435-7_25en_AU
local.publisher.urlhttp://link.springer.com/en_AU
local.type.statusAccepted Versionen_AU

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