Learning to Walk via Deep Reinforcement Learning

Deep reinforcement learning offers the promise of automatic acquisition of robotic control policies that directly map sensory inputs to low-level actions. In the domain of robotic locomotion, it could make it possible for locomotion skills to be learned with minimal engineering and without even needing to construct a model of the robot....More