Mattick says control methods such as model-predictive control assume the plant and its data are already available, so exploration is unnecessary.

“Again, it's basically it's the control versus reinforcement learning uh setup which I mentioned previously. In control or like model predictive or like non-linear model predictive control, you assume you have all the data that you have your plant, uh but you don't need to do any exploration in there, you it you just you you you hammer on this. Well for okay uh a model-based reinforcement learning you would also discover the world model and therefore you need to do exploration.”