Data efficient reinforcement learning and adaptive optimal perimeter control of network traffic dynamics

no code implementations • 13 Sep 2022 • C. Chen, Y. P. Huang, W. H. K. Lam, T. L. Pan, S. C. Hsu, A. Sumalee, R. X. Zhong

To handle these challenges, this work proposes an integral reinforcement learning (IRL) based approach to learning the macroscopic traffic dynamics for adaptive optimal perimeter control.

reinforcement-learning Reinforcement Learning (RL)