Practice Deep Reinforcement Learning - 9.7 | 9. Reinforcement Learning and Bandits | Advance Machine Learning
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9.7 - Deep Reinforcement Learning

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is the purpose of neural networks in deep reinforcement learning?

πŸ’‘ Hint: Think about how they help agents process information.

Question 2

Easy

Describe experience replay in one or two sentences.

πŸ’‘ Hint: Consider how students might review old tests to do better.

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 main advantage of using neural networks in DRL?

  • A) They reduce complexity
  • B) They can handle high-dimensional spaces
  • C) They are easier to implement

πŸ’‘ Hint: Think about the kinds of problems neural networks solve.

Question 2

True or False: Experience replay can make learning less efficient.

  • True
  • False

πŸ’‘ Hint: Consider if reviewing past inputs helps performance.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design a DRL agent for a video game environment. Explain how you would implement DQN and address potential challenges in training.

πŸ’‘ Hint: What game mechanics will influence your state and action definitions?

Question 2

Develop a comparison of DDPG and TD3 regarding their implementations in continuous spaces. What are the merits of choosing one over the other in specific environments?

πŸ’‘ Hint: Consider how exploration and stability affect learning in different scenarios.

Challenge and get performance evaluation