Xian-Wei Huang

Multi-agent meta-reinforcement learning based on contrastive predictive coding—For rapid adaptive traffic control after emergencies

A multi-agent meta-reinforcement learning framework is developed using Contrastive Predictive Coding for traffic state representation that maintained emergency vehicle priority while keeping the effect on regular traffic within a comparatively limited range under the evaluated emergency conditions.