Practice Deep Q-Networks (DQN) - 9.7.2 | 9. Reinforcement Learning and Bandits | Advance Machine Learning
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9.7.2 - Deep Q-Networks (DQN)

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is a Deep Q-Network?

πŸ’‘ Hint: Consider how traditional Q-learning works.

Question 2

Easy

What does experience replay help to address?

πŸ’‘ Hint: Think about the order of data during learning.

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 primary purpose of Deep Q-Networks?

  • To classify data
  • To approximate Q-values
  • To produce static outputs

πŸ’‘ Hint: Recall the role of Q-learning.

Question 2

True or False: Experience replay allows DQNs to use strictly recent experiences for training.

  • True
  • False

πŸ’‘ Hint: Think about how memory usage affects learning.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Imagine developing a DQN for a drone navigating an obstacle course. What modifications would you consider to enhance the learning process?

πŸ’‘ Hint: Think about how complex environments might benefit from additional stability mechanisms.

Question 2

Critique the effectiveness of DQNs in real-time decision-making scenarios. What alternative methods might be more suitable?

πŸ’‘ Hint: Reflect on the trade-offs between learning stability and adaptability.

Challenge and get performance evaluation