Deep Q-Network (DQN)

Instructions

In this exercise, you will implement Deep Q-Learning to solve OpenAI Gym's LunarLander environment. To begin, navigate to the exercise/ folder, and follow the instructions in Deep_Q_Network.ipynb.

(Alternatively, if you'd prefer to explore a complete implementation, enter the solution/ folder, and run the code in Deep_Q_Network_Solution.ipynb.)

After you are able to get the code working, try to change the parameters in the notebook, to see if you can get the agent to train faster! You may also like to implement prioritized experience replay, or use it as a starting point to implement a Double DQN or Dueling DQN!

Results

Resources

• Human-Level Control through Deep Reinforcement Learning
• Deep Reinforcement Learning with Double Q-Learning
• Dueling Network Architectures for Deep Reinforcement Learning
• Prioritized Experience Replay