The best way to learn and to avoid the illusion of competence is to test yourself. This will help you to find where you need to reinforce your knowledge.
Reinforcement learning is a framework for solving control tasks (also called decision problems) by building agents that learn from the environment by interacting with it through trial and error and receiving rewards (positive or negative) as unique feedback.
At every step:
In Reinforcement Learning, we need to balance how much we explore the environment and how much we exploit what we know about the environment.
Exploration is exploring the environment by trying random actions in order to find more information about the environment.
Exploitation is exploiting known information to maximize the reward.
Congrats on finishing this Quiz 🥳, if you missed some elements, take time to read again the chapter to reinforce (😏) your knowledge, but do not worry: during the course we’ll go over again of these concepts, and you’ll reinforce your theoretical knowledge with hands-on.