Rainbow Deep Q-Network

About

This is a repository for developing a Rainbow DQN. The starting seed is a miniproject from Udacity's Nanodegree in Reinforcement Learning. Implemented:

• Deep Q-Network with memory replay for learning (DQN)

• Double DQN (for some reason it still does not learn)

• Duel (Double) DQN (when not using DDQN it learns well, although a bit slower than the DQN)

• Importance sampling

The architecture of the network can be specified when instantiating the agent itself with a list of number of units (for fully-connected layers).

To see the application in another game: Picking up bananas

Get started

Python files Model and dqn_agent contain the definition of the model and the agents. The jupyter notebook shows how to use and train them

Requirements

• Numpy

• Matplotlib

• OpenAI Gym (LunarLander-v2)

• Pytorch

• pyvirtualdisplay

• box2d

• xvfb