# Deep-Reinforcement-Learning
<img src="dqn.gif" alt="alt text" width="300" height="300">

  -  Implemented Deep Q-Network (DQN) and Double DQN on the game of Breakout using the OpenAI Gym.
  -  Double DQN uses a target network to calculate the target Q-value (next state maximum) whereas the vanilla DQN uses the same network for computing Q values for both the current and next state.
  -  All calculations were run on Google Colab. Due to limitations in availability of computational resources, the model could be trained only for 500 episodes.