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: Which of the following interpretations of bias-variance tradeoff is the most accurate in the field of Reinforcement Learning?

Q2: Which of the following statements are true, when talking about models with bias and/or variance in RL?

Q3: Which of the following statements are true about Monte Carlo method?

Q4: How would you describe, with your own words, the Actor-Critic Method (A2C)?

Solution

The idea behind Actor-Critic is that we learn two function approximations:

1. A policy that controls how our agent acts (π)
2. A value function to assist the policy update by measuring how good the action taken is (q)

Q5: Which of the following statements are true about the Actor-Critic Method?

Q6: What is Advantage in the A2C method?

Solution

Instead of using directly the Action-Value function of the Critic as it is, we could use an Advantage function. The idea behind an Advantage function is that we calculate the relative advantage of an action compared to the others possible at a state, averaging them.

In other words: how taking that action at a state is better compared to the average value of the state

Congrats on finishing this Quiz 🥳, if you missed some elements, take time to read the chapter again to reinforce (😏) your knowledge.

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