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After reading up one Deep Deterministic Policy Gradient, I found this example on MATLAB:

https://www.mathworks.com/help/reinforcement-learning/ug/train-agent-to-control-flying-robot.html#TrainDDPGAgentToControlFlyingRobotExample-4

My question is the following: In DDPG, we plug in the Observation to our Actor to get our actions. The observations in the MATLAB environment are 7: x, y, dx, dy, sin, cos, dtheta. However, only x and y are assigned in the beginning. Does that mean that the rest are given random values before placed in the Critic Network? If my understanding is wrong, could someone please explain to me what is occurring in this model? Thank You

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