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I am testing different RL methods, and I know e.g that policy gradient method is supposed to have a high variance gradient which can cause trouble. I want to run a few different Deep RL algorithms, and see if I can see any patterns in the gradient. How can I visualize the gradient, and analyze it?

So far I have been using the average standard deviation, of the gradient, for every layer in my neural network and visualized it as a scalar with epoch on the x-axis. Is there a better way?

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  • $\begingroup$ Could you elaborate a bit more on what you expect to see from the gradients? I am curious as you seem that you are searching for something beyond simple statistics of the samples that estimate the gradients. $\endgroup$
    – Constantinos
    Oct 18, 2018 at 23:02

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