Hi all,
I’m confused about this line 56 in the actor_critic.py example. It also appears in Andrej Karpathy’s Pong w/Pixels code. Is there any good justification to normalize the reward targets on a per episode basis? My understanding is that normalizing reward values should be done over batches or over all previous episodic rewards encountered during training, in order to keep the RL task stationary. I haven’t been able to find anything regarding this per episode normalization in the literature.