Quiz

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.

Q1: What is Reinforcement Learning?

Solution

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.

Q2: Define the RL Loop

Exercise RL Loop

At every step:

Q3: What's the difference between a state and an observation?

Q4: A task is an instance of a Reinforcement Learning problem. What are the two types of tasks?

Q5: What is the exploration/exploitation tradeoff?

Solution

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 Exploitation Tradeoff

Q6: What is a policy?

Solution Policy

Q7: What are value-based methods?

Solution

Q8: What are policy-based methods?

Solution

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.