many different tasks right here and we have many policies now in essence they don't need to have some anything to do with each other for the theory of this paper but i can simplify this a bit of how they see the world so let's say you have an agent and the agent has been trained on simply that first task right here and has been trained using classic q learning reinforcement learning what not and that results in this particular policy and then the agent just from scratch you restarted again you run reinforcement learning just