This is a gym version of various games for reinforcenment learning.
Project description
# Gym Games This is a gym version of various games for reinforcenment learning.
For [PyGame learning environment](https://pygame-learning-environment.readthedocs.io/en/latest/user/games.html), the default observation is a non-visual state representation of the game.
For [MinAtar](https://github.com/kenjyoung/MinAtar), the default observation is a visual input of the game.
## Environments
PyGame learning environment: - Catcher-PLE-v0 - FlappyBird-PLE-v0 - Pixelcopter-PLE-v0 - PuckWorld-PLE-v0 - Pong-PLE-v0
MinAtar: - Asterix-MinAtar-v0 - Breakout-MinAtar-v0 - Freeway-MinAtar-v0 - Seaquest-MinAtar-v0 - Space_invaders-MinAtar-v0
## Installation
### Gym
Please read the instruction [here](https://github.com/openai/gym).
### PyGame
On OSX:
brew install sdl sdl_ttf sdl_image sdl_mixer portmidi pip install pygame
On Ubuntu:
sudo apt-get -y install python-pygame pip install pygame
Others: Please read the instruction [here](http://www.pygame.org/wiki/GettingStarted#Pygame%20Installation).
### PLE
pip install git+https://github.com/ntasfi/PyGame-Learning-Environment.git
## MinAtar
pip install git+https://github.com/kenjyoung/MinAtar.git
### gym-games
Install from source:
pip install git+https://github.com/qlan3/gym-games.git
Install it from PyPi:
pip install gym-games
## Example Run python test.py.
## References - [gym](https://github.com/openai/gym/tree/master/) - [gym-ple](https://github.com/lusob/gym-ple) - [SRNN](https://github.com/VincentLiu3/SRNN) - [MinAtar](https://github.com/kenjyoung/MinAtar)