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dc.contributor.author
Di Natale, Loris
dc.contributor.contactPerson
Di Natale, Loris
dc.contributor.dataCollector
Di Natale, Loris
dc.contributor.projectMember
Svetozarevic, Bratislav
dc.date.accessioned
2022-02-16T10:43:44Z
dc.date.available
2022-02-10T10:33:43Z
dc.date.available
2022-02-16T10:43:44Z
dc.date.issued
2021-02-16
dc.identifier.uri
http://hdl.handle.net/20.500.11850/531878
dc.identifier.doi
10.3929/ethz-b-000531878
dc.format
application/zip
en_US
dc.format
text/csv
en_US
dc.format
text/plain
en_US
dc.publisher
ETH Zurich
en_US
dc.rights.uri
http://opensource.org/licenses/CDDL-1.0
dc.title
Deep Reinforcement Learning for room temperature control: a black-box pipeline from data to policies
en_US
dc.type
Software
dc.rights.license
Common Development and Distribution License 1.0
ethz.size
1.92 MB
en_US
ethz.publication.place
Zurich
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02292 - NFS Dependable Ubiquitous Automation / NCCR Dependable Ubiquitous Automation
en_US
ethz.date.retentionend
indefinite
en_US
ethz.date.retentionendDate
n/a
ethz.relation.isSupplementTo
10.1088/1742-6596/2042/1/012004
ethz.date.deposited
2022-02-10T10:33:49Z
ethz.source
FORM
ethz.eth
no
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2022-02-16T10:44:40Z
ethz.rosetta.lastUpdated
2022-02-16T10:44:40Z
ethz.rosetta.versionExported
true
ethz.COinS
ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.atitle=Deep%20Reinforcement%20Learning%20for%20room%20temperature%20control:%20a%20black-box%20pipeline%20from%20data%20to%20policies&rft.date=2021-02-16&rft.au=Di%20Natale,%20Loris&rft.genre=unknown&rft.btitle=Deep%20Reinforcement%20Learning%20for%20room%20temperature%20control:%20a%20black-box%20pipeline%20from%20data%20to%20policies
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