Separated Proportional-Integral Lagrangian for Chance Constrained Reinforcement Learning

Safety is essential for reinforcement learning (RL) applied in real-world tasks like autonomous driving. Imposing chance constraints (or probabilistic constraints) is a suitable way to enhance RL safety under model uncertainty. Existing chance constrained RL methods like the penalty methods and the Lagrangian methods either exhibit periodic oscillations or learn an over-conservative or unsafe poli...