Welcome to the DEgym framework documentation! DEgym is a comprehensive framework for creating environments for reinforcement learning which is focused on systems governed by ODEs/DAEs
DEgym separates environment logic into two categories:
The framework provides the RL-related infrastructure, while users implement only the use-case-specific components by inheriting from abstract classes.
If you wish to contribute to DEGym, please refer to the contribution guidelines and follow the development installation for setting up the development environment with testing and linting tools.
This is the list of maintainers, who are in charge of triaging issues, reviewing and approving PRs from contributors.