I was reading this link , and saw some creative architectures for PPO.
I know the "No Free Lunch Theorem" and all, but what would be the logic/reasoning for why you would choose to have a different size/shape/depth for the actor vs. value func. networks in PPO?
I just came across this question, which is related but not the same. It asks about the utility of sharing parameters across the two networks, to which the answer is essentially "that might accelerate training by having less parameters". I think my question is distinct and more general.