Mini toolsDefinition
A combination of Q-learning with deep neural networks to handle high-dimensional state spaces.
Detailed Explanation
DQN combines Q-learning with deep neural networks to approximate the Q-function. It introduces several key innovations including experience replay and target networks to stabilize training. This allows reinforcement learning to work with high-dimensional input spaces like images.
Use Cases
Playing Atari games, robotic manipulation, autonomous systems, visual navigation tasks
