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I realized that the state is not normalized. This might not be a big issue, because if the state is never normalized, the networks should still be able to learn to make correct predictions from this. However, I think for fixed hyperparameters, an unnoramlized state could have a different influence on, for example, the magnitude of losses and also predictions right after the network weights are initialized.
I would very much appreciate someone else's insight on this and how much this may really change the resulting policy.
Cheers,
Rosa
The text was updated successfully, but these errors were encountered:
I realized that the state is not normalized. This might not be a big issue, because if the state is never normalized, the networks should still be able to learn to make correct predictions from this. However, I think for fixed hyperparameters, an unnoramlized state could have a different influence on, for example, the magnitude of losses and also predictions right after the network weights are initialized.
I would very much appreciate someone else's insight on this and how much this may really change the resulting policy.
Cheers,
Rosa
The text was updated successfully, but these errors were encountered: