Practice Advantage Actor-Critic (A2C) - 9.6.4 | 9. Reinforcement Learning and Bandits | Advance Machine Learning
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9.6.4 - Advantage Actor-Critic (A2C)

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does the actor do in the A2C algorithm?

πŸ’‘ Hint: Think of the action selector.

Question 2

Easy

What is the role of the critic in A2C?

πŸ’‘ Hint: It's the evaluator of performance.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What is the role of the actor in A2C?

  • Selects actions
  • Evaluates actions
  • Calculates rewards

πŸ’‘ Hint: Remember who makes the decisions.

Question 2

The advantage function is used to:

  • True
  • False

πŸ’‘ Hint: Think about its impact on the learning process.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

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.

πŸ’‘ Hint: Consider the specific actions and states in a smart home.

Question 2

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

πŸ’‘ Hint: Reflect on common reinforcement learning challenges.

Challenge and get performance evaluation