Dynamic traffic aware active queue management using deep reinforcement learning

Traditional design of active queue management (AQM) assumes a fixed model at an operating point and lacks planning. AQMs like controlled delay provide some planning but are insensitive to dynamic traffic. In this Letter, the authors propose dynamic traffic aware AQM with deep reinforcement learning to expand the model on a grid of operati...更多