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.
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/300253/image.png)
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Accepted Answer
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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