Describe the Deep Q-Network (DQN) algorithm.
The Deep Q-Network (DQN) algorithm is a seminal reinforcement learning algorithm developed by DeepMind in 2013 that combines deep learning with Q-learning. It extends traditional Q-learning to handle high-dimensional state spaces by using deep neural networks to approximate the action-value function (Q-function).
Here's a step-by-step description of the DQN algorithm :
* Experience Replay
* Target Network
* Q-Network Architecture
* Q-Learning Update
* Exploration-Exploitation
