Practice Deep Q-networks (dqn) (9.7.2) - Reinforcement Learning and Bandits
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Deep Q-Networks (DQN)

Practice - Deep Q-Networks (DQN)

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is a Deep Q-Network?

💡 Hint: Consider how traditional Q-learning works.

Question 2 Easy

What does experience replay help to address?

💡 Hint: Think about the order of data during learning.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the primary purpose of Deep Q-Networks?

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

💡 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

💡 Hint: Think about how memory usage affects learning.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

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

💡 Hint: Think about how complex environments might benefit from additional stability mechanisms.

Challenge 2 Hard

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

💡 Hint: Reflect on the trade-offs between learning stability and adaptability.

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Reference links

Supplementary resources to enhance your learning experience.