10.3.2 - Deep Q-Networks (DQN)
Enroll to start learning
You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.
Practice Questions
Test your understanding with targeted questions
What does DQN stand for?
💡 Hint: What does the 'D' in DQN imply?
Name one technique used in DQNs to stabilize training.
💡 Hint: Think about storing past experiences or using an additional network.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What does DQN primarily utilize to approximate Q-values?
💡 Hint: Think about why Q-learning needed an upgrade.
True or False: DQNs can directly learn from raw pixel input.
💡 Hint: Consider the applications of DQNs in gaming.
1 more question available
Challenge Problems
Push your limits with advanced challenges
Design a pseudo-code for a simple DQN algorithm that incorporates experience replay and a target network.
💡 Hint: Consider steps involved in maintaining and updating both networks.
Critically analyze the impact of experience replay on the performance of a DQN agent in a specific scenario, such as playing a complex game.
💡 Hint: Reflect on both the pros and cons in the context of dynamic environments.
Get performance evaluation
Reference links
Supplementary resources to enhance your learning experience.