Ruo-Qi Wen

Multi-Agent Uncertainty-Aware Pessimistic Model-Based Reinforcement Learning for Connected Autonomous Vehicles

MA-PMBRL, a novel Multi-Agent Pessimistic Model-Based Reinforcement Learning framework for CAVs, incorporating a max-min optimization approach to enhance robustness and decision-making is proposed, demonstrating that the proposed framework represents a significant step toward scalable, efficient, and reliable multi-age...