Reinforcement Learning for Traffic Signal Control Optimization
Author: | Henri Meess, Jeremias GernerORCiD, Daniel Hein, Stefanie SchmidtnerORCiD, Gordon ElgerORCiD |
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Subtitle (English): | A Concept for Real-World Implementation |
Language: | English |
Document Type: | Conference Paper |
Conference: | AAMAS ' 22: International Conference on Autonomous Agents and Multi-Agent Systems, Virtual Event New Zealand, 9.-13.05.2022 |
Year of first Publication: | 2022 |
published in (English): | AAMAS '22: Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems |
Publisher: | International Foundation for Autonomous Agents and Multiagent Systems |
Place of publication: | Richland |
ISBN: | 978-1-4503-9213-6 |
First Page: | 1699 |
Last Page: | 1701 |
Review: | peer-review |
Open Access: | nein |
Tag: | DRL; MARL; Multi-Agent Reinforcement Learning in real-world; multimodal traffic; traffic optimization |
URL: | https://dl.acm.org/doi/10.5555/3535850.3536081 |
Faculties / Institutes / Organizations: | Fakultät Elektro- und Informationstechnik |
AImotion Bavaria | |
Fraunhofer-Anwendungszentrum "Vernetzte Mobilität und Infrastruktur" | |
Release Date: | 2022/08/02 |