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.
This is the implementation of training a RL agent to play the mighty game of Pong.
In order to train a RL agent to play the mighty game of Pong, you need to run it on Python3 and install:
- gym
pip install gym
- gym atari
pip install "gym[atari]"
- numpy
pip install numpy
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
- Faza Fahleraz https://github.com/ffahleraz
- Nicholas Rianto Putra https://github.com/nicholaz99
- Abram Perdanaputra https://github.com/abrampers
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
- Deep Reinforcement Learning: Pong from Pixels
- 220 Logistic Regression
- CS231n Convolutional Neural Networks for Visual Recognition
- Lecture 14 | Deep Reinforcement Learning
- TensorFlow and deep reinforcement learning, without a PhD (Google I/O '18)
- Building a Convolutional Neural Network in Python with Tensorflow