Model-based Constrained Reinforcement Learning using Generalized Control Barrier Function
Haitong Ma,Jianyu Chen,Shengbo Eben,Ziyu Lin,Yang Guan,Yangang Ren,Sifa Zheng,Haitong Ma,Jianyu Chen,Shengbo Eben,Ziyu Lin,Yang Guan,Yangang Ren,Sifa Zheng
Model information can be used to predict future trajectories, so it has huge potential to avoid dangerous regions when applying reinforcement learning (RL) on real-world tasks, like autonomous driving. However, existing studies mostly use model-free constrained RL, which causes inevitable constraint violations. This paper proposes a model-based feasibility enhancement technique of constrained RL, ...
