Low-fidelity high-performance ship simulator built with pygame / pymunk with OpenAI gym wrapper and example scripts for stable-baselines and rllib for training RL agents.
This gym and the accompanying scripts allow you to quickly iterate over different ideas
For questions / comments: do not hesitate to do so via the issues or a direct PM to gerardsimons.
Python 3.6 is required. Make sure you are not using Python 3.7. It's not supported by ray / rllib and a few others at moment of writing.
First make sure you meet the requirements for each below, then try and do a
pip install -r requirements.txt
The game is built with pygame and pymunk. pygame is a library that allows for creating windows and drawing primitives. Pymunk is needed for the physics. Both should be pip installable. If not visit their respective websites for more info.
stable-baselines has specific prerequisites listed in the README, make sure you meet those before continuing.
pip install ray[rllib] should do. See specific version in requirements.txt
If you get an issue like this:
redis.exceptions.DataError: Invalid input of type: 'NoneType'. Convert to a byte, string or number first.
Revert back to Redis 2:
pip install -U redis==2.10.6
Easiest thing is to run the jupyter notebook. Even though the code is mostly just imports from existing scripts it explains quite a bit in the Markdown cells.
Run from the repo root:
jupyter notebook notebooks
NOTE: It seems some of the code doesn't do to well in a notebook cell. If you prefer you can also run the scripts in train manually by calling them as modules.
For example to run the stable-baselines PPO script do
python -m train.stable_baselines.ppo
To run the PPO trainer of RLLib do:
python -m train.rllib.ppo
Or the population based training schedule:
python -m train.rllib.pbt
Again feel free to discuss ideas or propose new features via the issues tab!
If you have an idea for a feature, feel free to create your own feature branch from dev:
git checkout -b feature/<featuer_name> dev
Once finished, you can do a pull request.