— The aquisition and improvement of motor skills and control policies for robotics from trial and error is of essential importance if robots should ever leave precisely pre-struc...
— This paper proposes a learning framework for a CPG-based biped locomotion controller using a policy gradient method. Our goal in this study is to develop an efficient learning...
Takamitsu Matsubara, Jun Morimoto, Jun Nakanishi, ...
This paper investigates a novel model-free reinforcement learning architecture, the Natural Actor-Critic. The actor updates are based on stochastic policy gradients employing Amari...
Recently, actor-critic methods have drawn much interests in the area of reinforcement learning, and several algorithms have been studied along the line of the actor-critic strategy...
We present four new reinforcement learning algorithms based on actor-critic and natural-gradient ideas, and provide their convergence proofs. Actor-critic reinforcement learning m...
Shalabh Bhatnagar, Richard S. Sutton, Mohammad Gha...