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
Improved Learning in Multi-Agent Pursuer-Evader UAV Scenari..:
, In:
2024 International Conference on Unmanned Aircraft Systems (ICUAS)
,
Cabral, Kleber
;
Delamer, Jean-Alexis
;
Rabbath, Camille-Alain
... - p. 144-151 , 2024
Link:
https://doi.org/10.1109/ICUAS60882.2024.10557110
RT T1 <cTitle>2024 International Conference on Unmanned Aircraft Systems (ICUAS)</cTitle>: T1 <Title>Improved Learning in Multi-Agent Pursuer-Evader UAV Scenarios via Mechanism Design and Deep Reinforcement Learning</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10557110&Exemplar=1&LAN=DE A1 Cabral, Kleber A1 Delamer, Jean-Alexis A1 Rabbath, Camille-Alain A1 Lechevin, Nicolas A1 Williams, Craig A1 Givigi, Sidney YR 2024 SN 2575-7296 K1 Training K1 Navigation K1 Design methodology K1 Games K1 Deep reinforcement learning K1 Autonomous aerial vehicles K1 Autonomous agents K1 mechanism design K1 deep reinforcement learning K1 multi-agent systems K1 reward design SP 144 OP 151 LK http://dx.doi.org/https://doi.org/10.1109/ICUAS60882.2024.10557110 DO https://doi.org/10.1109/ICUAS60882.2024.10557110 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
