I used a deep reinforcement learning toolbox to path planning of a robot, including the DDPG algorithm. My scenario is that the robot starts from a random position and reaches the random goal location. After training, the result is a fixed path! And with changing the goal position, the path does not change. It is as if the network has learned only one path. The Drop-out layer is used in the network structure.
Does anyone have any idea what went wrong?
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