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View Code? Open in Web Editor NEWHacks for training RL systems from John Schulman's lecture at Deep RL Bootcamp (Aug 2017)
Hacks for training RL systems from John Schulman's lecture at Deep RL Bootcamp (Aug 2017)
In the section Policy Gradients diagnostics, it is mentioned :
If KL is .01 then very small.
If 10 then too much.
I couldn't find the given values in the slides of the original talk. Where these values are from ?
Also, in the previous part (about entropy), you mentioned how to fix the problem with fast-dropping entropy, and it is really helpful.
Does anyone know how to fix the problem of KL divergence being too low ?
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