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Comment by gyrovagueGeist

Does anyone know why they added minibatch advantage normalization (or when it can be useful)?

The paper they cite "What matters in on-policy RL" claims it does not lead to much difference on their suite of test problems, and (mean-of-minibatch)-normalization doesn't seem theoretically motivated for convergence to the optimal policy?

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