Reinforcement Learning (RL) methods are typically sample-inefficient, making it challenging
to train and deploy RL-policies in real world robots. Even a robust policy trained in …

Policy gradient methods are a vital ingredient behind the success of modern reinforcement
learning. Modern policy gradient methods, although successful, introduce a residual error in …