Practice Advantage Actor-critic (a2c) (9.6.4) - Reinforcement Learning and Bandits
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Advantage Actor-Critic (A2C)

Practice - Advantage Actor-Critic (A2C)

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does the actor do in the A2C algorithm?

💡 Hint: Think of the action selector.

Question 2 Easy

What is the role of the critic in A2C?

💡 Hint: It's the evaluator of performance.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the role of the actor in A2C?

Selects actions
Evaluates actions
Calculates rewards

💡 Hint: Remember who makes the decisions.

Question 2

The advantage function is used to:

True
False

💡 Hint: Think about its impact on the learning process.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Imagine you are designing a reinforcement learning agent for a smart home system. How would you implement A2C in this scenario? Discuss the components involved and their roles.

💡 Hint: Consider the specific actions and states in a smart home.

Challenge 2 Hard

Consider a scenario where an A2C algorithm performs poorly initially. Discuss factors that might lead to poor performance and how you would address them.

💡 Hint: Reflect on common reinforcement learning challenges.

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Reference links

Supplementary resources to enhance your learning experience.