DeepLearningFlappyBird

 Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).

Using Deep Q-Network to Learn How To Play Flappy Bird

7 mins version: DQN for flappy bird

Overview

This project follows the description of the Deep Q Learning algorithm described in Playing Atari with Deep Reinforcement Learning [2] and shows that this learning algorithm can be further generalized to the notorious Flappy Bird.

Installation Dependencies:

• Python 2.7 or 3
• TensorFlow 0.7
• pygame
• OpenCV-Python

How to Run?

git clone https://github.com/yenchenlin1994/DeepLearningFlappyBird
cd DeepLearningFlappyBird
python deep_q_network.py

What is Deep Q-Network?

It is a convolutional neural network, trained with a variant of Q-learning, whose input is raw pixels and whose output is a value function estimating future rewards.

For those who are interested in deep reinforcement learning, I highly recommend to read the following post:

Demystifying Deep Reinforcement Learning

from  https://github.com/yenchenlin/DeepLearningFlappyBird