Reinforcement Learning Algorithms with Python

Comparing IL and RL

Let's go more in-depth with the IL approach by highlighting the differences vis-à-vis RL. This contrast is very important. In imitation learning, the learner is not aware of any reward. This constraint can have very big implications.

Going back to our example, the apprentice can only replicate the expert's moves as closely as possible, be it in a passive or an active way. Not having objective rewards from the environment, they are constrained to the subjective supervision of the expert. Thus, even if they wanted to, they aren't able to improve and understand the teacher's reasoning.

So, IL should be seen as a way to copy the moves of the expert but without knowing its main goal. In our example, it's as if the young driver ...