Mean-Field-Aided Multiagent Reinforcement Learning for Resource Allocation in Vehicular Networks
Published in IEEE Internet of Things Journal, 2023
Recommended citation: Hengxi Zhang, Chengyue Lu, Huaze Tang, Xiaoli Wei, Le Liang, Ling Cheng, Wenbo Ding, and Zhu Han. " Mean-Field-Aided Multiagent Reinforcement Learning for Resource Allocation in Vehicular Networks." IEEE Internet of Things Journal 10, no. 3 (2022): 2667-2679. https://ieeexplore.ieee.org/abstract/document/9919273
In this article, we propose a novel method MF-MARL that combines mean-field game with MARL to decrease the computational complexity in a decentralized multi-agent system while maintaining a near-optimal performance.
Hengxi Zhang, Chengyue Lu, Huaze Tang, Xiaoli Wei, Le Liang, Ling Cheng, Wenbo Ding, and Zhu Han. “Mean-Field-Aided Multiagent Reinforcement Learning for Resource Allocation in Vehicular Networks.” IEEE Internet of Things Journal 10, no. 3 (2022): 2667-2679.