How to train DDPG episode reward more better?
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I'm training a DDPG agent from the Reinforcement Learning toolbox. But as you can see, my episode reward never change. I try so many way to fix this problem. Like change the netwoek, Gradient Threshold, Learning Rate. But the result will be the same. I check my reward funtion, if the situation is eligible I will give it some reward or penalty. But its reward is always be same.
Is my condtion have some problem? Or my results are not input into the model? I dont have anyway to do.
2 Comments
Emmanouil Tzorakoleftherakis
on 28 Feb 2020
How did you set the IsDone flag? This may lead to premature episode termination
Guoge Tan
on 25 May 2020
Hi, sorry to bother you, but I'd like to ask if your problem is solved or not? I‘m working on a path planning problem using the Reinforcement Learning toolbox on MATLAB R2020a and I also encountered a problem similar to yours.
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