谢远昌

Balancing adversariality and naturalness in autonomous vehicle testing scenario generation via multi-objective reinforcement learning

Reinforcement learning (RL)-based adversarial scenario generation through dynamic agent–environment interactions has emerged as a promising approach for accelerating autonomous vehicle (AV) testing. However, existing RL approaches struggle to balance adversariality and naturalnes...