FedLight: Federated Reinforcement Learning for Autonomous Multi-Intersection Traffic Signal Control

Although Reinforcement Learning (RL) has been successfully applied in traffic control, it suffers from the problems of high average vehicle travel time and slow convergence to optimized solutions. This is because, due to the scalability restriction, most existing RL-based methods focus on the optimi...

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Vydáno v:	2021 58th ACM/IEEE Design Automation Conference (DAC) s. 847 - 852
Hlavní autoři:	Ye, Yutong, Zhao, Wupan, Wei, Tongquan, Hu, Shiyan, Chen, Mingsong
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	IEEE 05.12.2021
Témata:	Advantage Actor-Critic Collaboration Collaborative work Design automation Federated Reinforcement Learning Neural Network Process control Reinforcement learning Scalability Traffic control Traffic Signal Control
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