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Actor-Critic Methods are very useful reinforcement learning techniques. Actor-critic methods are most useful for applications in robotics as they allow software to output continuous, rather than discrete actions. This enables control of electric motors to actuate movement in robotic systems, at the expense of increased computational complexity. We just released...