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
Sample-Efficient Learning for Industrial Assembly using Qgr..:
, In:
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
,
Hoppe, Sabrina
;
Giftthaler, Markus
;
Krug, Robert
. - p. 9080-9087 , 2020
Link:
https://doi.org/10.1109/IROS45743.2020.9341390
RT T1
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
: T1
Sample-Efficient Learning for Industrial Assembly using Qgraph-bounded DDPG
UL https://suche.suub.uni-bremen.de/peid=ieee-9341390&Exemplar=1&LAN=DE A1 Hoppe, Sabrina A1 Giftthaler, Markus A1 Krug, Robert A1 Toussaint, Marc YR 2020 SN 2153-0866 K1 Shafts K1 Uncertainty K1 Training data K1 Reinforcement learning K1 Task analysis K1 Tuning K1 Convergence SP 9080 OP 9087 LK http://dx.doi.org/https://doi.org/10.1109/IROS45743.2020.9341390 DO https://doi.org/10.1109/IROS45743.2020.9341390 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)