Building a Pong playing AI

This repository contains the resources needed for the tutorial, Building a Pong playing AI in just 1 hour(Plus 4 days training time)

Requirements

Python

Either 2 or 3 is fine.

PyGame

Download which ever version matches the version of Python you plan on using.

TensorFlow

Again match the version.

Matplotlib

Match version

Other requirments options

Tensorflow requires an NVidea GPU and only runs on Linux/Mac so if you don't have these Theano is an option. The examples are all in Tensorflow, but that translates very easily to Theano and we have an example Q-learning Theano implementation that can be extended to work with Pong.

Python

Either 2 or 3 is fine.

PyGame

Download which ever version matches the version of Python you plan on using.

Theano

Download anaconda

On windows cmd:

>> conda install mingw libpython numpy

Checkout Theano

git clone https://github.com/Theano/Theano.git

>> cd Theano
>> python setup.py develop

Set your project interpreter to be using anaconda python

Resources

PyGame Player

Used for running reinforcement learning agents against PyGame

PyGame Pong

PyGame implementation of pong

PyGame Half Pong

Even pong can be hard if your just a machine. 
Half pong is a simplified version of pong, if you can believe it.
The score and other bits of noise are removed from the game. 
There is only 1 bar and it is only 80x80 pixels which speeds up training and removes the need to downsize the screen 

Examples

Random Half Pong player

Random With Base Half Pong player

MLP Half Pong player

Tensor flow Q learning

Theano flow Q learning

MLP Q learning Half Pong player

Convolutional network Half Pong player