midQ-Learning
What is Deep Q-Network (DQN)?
Updated May 17, 2026
Short answer
DQN uses neural networks to approximate Q-values.
Deep explanation
DQN combines Q-learning with deep neural networks and uses experience replay and target networks to stabilize training.
Real-world example
Used in self-playing agents like Atari game AI.
Common mistakes
- Training without target network causing instability.
Follow-up questions
- What is experience replay?
- Why use target networks?