Playing Flappy Bird Using Deep Reinforcement Learning (Based on Deep Q Learning DQN)

Train Video

Include NIPS 2013 version and Nature Version DQN

Run the code: python3 FlappyBirdDQN.py

Since the DQN code is a unique class, you can use it to play other games.

About the code

As a reinforcement learning problem, we knows we need to obtain observations and output actions, and the 'brain' do the processing work.

Therefore, you can easily understand the BrainDQN.py code. There are three interfaces:

1. getInitState() for initialization
2. getAction()
3. setPerception(nextObservation,action,reward,terminal)

the game interface just need to be able to feed the action to the game and output observation,reward,terminal

Disclaimer

This work is based on the repo: floodsung/DRL-FlappyBird