Deep Adaptive Algorithms for Local Urban Traffic Control: Deep Reinforcement Learning with DQN-Reference-Cited by-同舟云学术

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Deep Adaptive Algorithms for Local Urban Traffic Control: Deep Reinforcement Learning with DQN

Published:2024-01-04 Issue: Volume: Page:592-598
ISSN:
Container-title:2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT)
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Author:

Subba Rao P V R¹,Murthy Polisetty Venkata Ramana¹,Jayanth K Krishna¹,Sai Manoj N V¹,Mohith Vankadari¹,Kumar R Prasanna¹

Affiliation:

1. Amrita Vishwa Vidyapeetham, School of Computing,Computer Science and Engineering,Chennai

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10467178/10467214/10467630.pdf?arnumber=10467630

Reference19 articles.

1. Model-Based Deep Reinforcement Learning with Traffic Inference for Traffic Signal Control

2. A Novel Multi-Agent Deep RL Approach for Traffic Signal Control

3. Improving the generalizability and robustness of large-scale traffic signal control;Shi;arXiv.org,2023

4. Multi-Objective Traffic Signal Control Using Network-Wide Agent Coordinated Reinforcement Learning

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