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A Multi-Agent Deep Reinforcement Learning Coordination Framework for
  Connected and Automated Vehicles at Merging Roadways

A Multi-Agent Deep Reinforcement Learning Coordination Framework for Connected and Automated Vehicles at Merging Roadways

23 September 2021
S. Nakka
Behdad Chalaki
Andreas A. Malikopoulos
ArXivPDFHTML

Papers citing "A Multi-Agent Deep Reinforcement Learning Coordination Framework for Connected and Automated Vehicles at Merging Roadways"

4 / 4 papers shown
Title
AI Recommendation Systems for Lane-Changing Using Adherence-Aware Reinforcement Learning
AI Recommendation Systems for Lane-Changing Using Adherence-Aware Reinforcement Learning
Weihao Sun
Heeseung Bang
Andreas A. Malikopoulos
106
0
0
28 Apr 2025
CorrA: Leveraging Large Language Models for Dynamic Obstacle Avoidance of Autonomous Vehicles
Shanting Wang
Panagiotis Typaldos
Andreas A. Malikopoulos
47
0
0
03 Mar 2025
Multi-Agent Reinforcement Learning for Connected and Automated Vehicles
  Control: Recent Advancements and Future Prospects
Multi-Agent Reinforcement Learning for Connected and Automated Vehicles Control: Recent Advancements and Future Prospects
Min Hua
Dong Chen
Xinda Qi
Kun Jiang
Z. Liu
Quan Zhou
Hongming Xu
16
10
0
18 Dec 2023
Multi-Agent Reinforcement Learning Guided by Signal Temporal Logic
  Specifications
Multi-Agent Reinforcement Learning Guided by Signal Temporal Logic Specifications
Jiangwei Wang
Shuo Yang
Ziyan An
Songyang Han
Zhili Zhang
Rahul Mangharam
Meiyi Ma
Fei Miao
29
8
0
11 Jun 2023
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