/pong

An implementation of Reinforcement Learning on the classic game of Pong

Primary LanguagePython

Pong

Pong is one of the earliest arcade video games. It is a table tennis sports game featuring simple two-dimensional graphics. The game was originally manufactured by Atari, which released it in 1972. Allan Alcorn created Pong as a training exercise assigned to him by Atari co-founder Nolan Bushnell.

Introduction

This is the implementation of training a RL agent to play the mighty game of Pong.

Requirements

In order to train a RL agent to play the mighty game of Pong, you need to run it on Python3 and install:

  1. gym
pip install gym
  1. gym atari
pip install "gym[atari]"
  1. numpy
pip install numpy

Train RL agent

Run this command on your terminal

python pong.py

Arguments :
-l, --load <pkl_path> #path to the saved model to load from
-s, --save <folder_path> #path to the folder to save model
-r, --render #whether to render the environment or not

Authors

  1. Faza Fahleraz https://github.com/ffahleraz
  2. Nicholas Rianto Putra https://github.com/nicholaz99
  3. Abram Perdanaputra https://github.com/abrampers

Words from Authors

Thanks to Andrej Karpathy for his amazing blogpost about Deep Reinforcement Learning: Pong from Pixels.

"It shouldn’t work, but amusingly we live in a universe where it does" - Andrej Karpathy

References