Before revision:  We use reinforcement learning to train a high-level gait policy that specifies the contact schedules of each foot, while the low-level Model Predictive Controller (MPC) optimizes the motor torques so that the robot can walk at a desired velocity using that gait pattern.
After revision:  We use reinforcement learning to train a high-level gait policy that specifies the contact schedules of each foot, while the low-level whole-body controller optimizes the motor torques so that the robot can walk at a desired velocity using that gait pattern.