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This is a gym version of various games for reinforcenment learning.

Project description

# Gym Games

This is a gym compatible version of various games for reinforcenment learning.

For [PyGame Learning Environment](, the default observation is a non-visual state representation of the game.

For [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](

### Pygame

### PyGame Learning Environment

pip install git+

## MinAtar

pip install git+

### Gym-games

  • Install from source:

    pip install git+

  • Install from PyPi:

    pip install gym-games

## Example

Run python

## Cite

Please use this bibtex to cite this repo:

@misc{gym-games, author = {Qingfeng, Lan}, title = {Gym Compatible Games for Reinforcenment Learning}, year = {2019}, publisher = {GitHub}, journal = {GitHub Repository}, howpublished = {url{}} }

## References

Project details

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