In his lecture 5 of the course "Reinforcement Learning", David Silver introduced GLIE Monte-Carlo Control.
I understand that we do policy evaluation for one step and then policy improvement. My question is how does the improved policy come into play in this GLIE algorithm?
Gt (return) based on the policy somehow? is that where the new policy comes in?
Asked another way, how are policy evaluation and policy improvement connected in this image?