I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
Deep Reinforcement Learning for Playing 2.5D Fighting Games:
, In:
2018 25th IEEE International Conference on Image Processing (ICIP)
,
Li, Yu-Jhe
;
Chang, Hsin-Yu
;
Lin, Yu-Jing
.. - p. 3778-3782 , 2018
Link:
https://doi.org/10.1109/ICIP.2018.8451491
RT T1
2018 25th IEEE International Conference on Image Processing (ICIP)
: T1
Deep Reinforcement Learning for Playing 2.5D Fighting Games
UL https://suche.suub.uni-bremen.de/peid=ieee-8451491&Exemplar=1&LAN=DE A1 Li, Yu-Jhe A1 Chang, Hsin-Yu A1 Lin, Yu-Jing A1 Wu, Po-Wei A1 Wang, Yu-Chiang Frank YR 2018 SN 2381-8549 K1 Games K1 Training K1 Machine learning K1 Three-dimensional displays K1 Two dimensional displays K1 Servers K1 Standards K1 Deep reinforcement learning K1 2.5D K1 game SP 3778 OP 3782 LK http://dx.doi.org/https://doi.org/10.1109/ICIP.2018.8451491 DO https://doi.org/10.1109/ICIP.2018.8451491 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)