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Multi-Agent Reinforcement Learning for Energy Harvesting Two-Hop Communications With a Partially Observable System State

Ortiz Jimenez, Andrea Patricia ; Weber, Tobias ; Klein, Anja (2021):
Multi-Agent Reinforcement Learning for Energy Harvesting Two-Hop Communications With a Partially Observable System State.
In: IEEE Transactions on Green Communications and Networking, 5 (1), pp. 442-456. IEEE, e-ISSN 2473-2400,
DOI: 10.1109/TGCN.2020.3026453,
[Article]

Item Type: Article
Erschienen: 2021
Creators: Ortiz Jimenez, Andrea Patricia ; Weber, Tobias ; Klein, Anja
Title: Multi-Agent Reinforcement Learning for Energy Harvesting Two-Hop Communications With a Partially Observable System State
Language: English
Journal or Publication Title: IEEE Transactions on Green Communications and Networking
Journal volume: 5
Number: 1
Publisher: IEEE
Uncontrolled Keywords: emergenCITY_KOM, emergenCITY_KOM2
Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Communications Engineering
LOEWE
LOEWE > LOEWE-Zentren
LOEWE > LOEWE-Zentren > emergenCITY
TU-Projects: HMWK|III L6-519/03/05.001-(0016)|emergenCity TP Bock
Date Deposited: 22 Mar 2021 09:40
DOI: 10.1109/TGCN.2020.3026453
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