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
Multi-Agent Deep Reinforcement Learning For Real-World Traf..:
, In:
2022 IEEE 20th International Conference on Industrial Informatics (INDIN)
,
Friesen, Maxim
;
Tan, Tian
;
Jasperneite, Jurgen
. - p. 162-169 , 2022
Link:
https://doi.org/10.1109/INDIN51773.2022.9976109
RT T1
2022 IEEE 20th International Conference on Industrial Informatics (INDIN)
: T1
Multi-Agent Deep Reinforcement Learning For Real-World Traffic Signal Controls - A Case Study
UL https://suche.suub.uni-bremen.de/peid=ieee-9976109&Exemplar=1&LAN=DE A1 Friesen, Maxim A1 Tan, Tian A1 Jasperneite, Jurgen A1 Wang, Jie YR 2022 K1 Deep learning K1 Performance evaluation K1 Roads K1 Reinforcement learning K1 Data models K1 Real-time systems K1 Timing K1 traffic signal control K1 deep reinforcement learning K1 vissim SP 162 OP 169 LK http://dx.doi.org/https://doi.org/10.1109/INDIN51773.2022.9976109 DO https://doi.org/10.1109/INDIN51773.2022.9976109 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)