# Sample complexity of deep reinforcement learning agents on smaller state spaces versus zero-padded state spaces

If I train two agents, one on environment A and one on environment A', where A' is just environment A padded with 10 rows of zeros, what can I predict will happen in terms of relative sample complexity of each agent?

Let's say the algorithm is soft actor critic.