Why is the DDPG episode rewards never change during the whole training process?
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Guoge Tan
on 25 May 2020
Commented: Shahriar
on 29 Jun 2022
I'm training a DDPG agent using the Reinforcement Learning toolbox on MATLAB R2020a for a path planning problem. But as you can see, the DDPG episode rewards and average rewards never change during 5000 episodes. I used a simple neural networks with 20 neurons and three layers, the learning rate is set to 0.01, and the Gradient Threshold is 1. Then I try to set weights and bias for fully connected layers and change my reward function, but the result is the same.
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Emmanouil Tzorakoleftherakis
on 26 May 2020
Looks like the scale between Q0 and episode reward is very different. Try unchecking "Show Episode Q0" to see of the episode reward changes. I would then simplify the critic network to make sure it outputs values in a similar scale as the episode reward.
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