Deep Learning for Go
dc.contributor.author
Rosenthal, Jonathan
dc.date.accessioned
2017-06-14T09:00:49Z
dc.date.available
2017-06-14T09:00:49Z
dc.date.issued
2016
dc.identifier.uri
http://hdl.handle.net/20.500.11850/156354
dc.identifier.doi
10.3929/ethz-a-010891076
dc.format
application/pdf
dc.language.iso
en
dc.publisher
ETH-Zürich
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.subject
MASCHINELLES LERNEN (KÜNSTLICHE INTELLIGENZ)
dc.subject
PROBLEMLÖSEN + PLANEN + SUCHEN (KÜNSTLICHE INTELLIGENZ)
dc.subject
NEURONALE NETZWERKE + KONNEKTIONISMUS (KÜNSTLICHE INTELLIGENZ)
dc.subject
GO, JAPANISCHES BRETTSPIEL (UNTERHALTUNG)
dc.subject
MACHINE LEARNING (ARTIFICIAL INTELLIGENCE)
dc.subject
PROBLEM SOLVING + PLAN GENERATION + SEARCH (ARTIFICIAL INTELLIGENCE)
dc.subject
NEURAL NETWORKS + CONNECTIONISM (ARTIFICIAL INTELLIGENCE)
dc.subject
GO, JAPANESE BOARD GAME (ENTERTAINMENT)
dc.title
Deep Learning for Go
dc.type
Bachelor Thesis
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2017
ethz.size
1 Online-Ressource
ethz.code.ddc
DDC - DDC::0 - Computer science, information & general works::004 - Data processing, computer science
ethz.notes
Bachelorarbeit. Eidgenössische Technische Hochschule Zürich. 2016.
ethz.identifier.nebis
010891076
ethz.publication.place
Zürich
ethz.publication.status
published
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02150 - Dep. Informatik / Dep. of Computer Science
ethz.date.deposited
2017-06-14T09:04:16Z
ethz.source
ECOL
ethz.identifier.importid
imp59366bb18797587695
ethz.ecolpid
eth:50876
ethz.eth
yes
ethz.availability
Open access
ethz.rosetta.installDate
2017-07-18T19:49:40Z
ethz.rosetta.lastUpdated
2021-02-14T16:57:33Z
ethz.rosetta.versionExported
true
ethz.COinS
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Bachelor Thesis [168]