@misc{tassel2021reinforcement,
      title={A Reinforcement Learning Environment For Job-Shop Scheduling}, 
      author={Pierre Tassel and Martin Gebser and Konstantin Schekotihin},
      year={2021},
      eprint={2104.03760},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

├── README.md                 <- The top-level README for developers using this project.
└── JSS
    ├── dispatching_rules/      <- Contains the code to run the disptaching rule FIFO and MWTR.
    ├── instances/              <- All Taillard's instances + 5 Demirkol instances.
    ├── randomLoop/             <- A random loop with action mask, usefull to debug environment and
    |                             to check if our agent learn.
    ├── CP.py                   <- OR-Tool's cp model for the JSS problem.
    ├── CustomCallbacks.py      <- A special RLLib's callback used to save the best solution found.
    ├── default_config.py       <- default config used for the disptaching rules.
    ├── env_wrapper.py          <- Envrionment wrapper to save the action's of the best solution found
    ├── main.py                 <- PPO approach, the main file to call to reproduce our approach.
    └── models.py               <- Tensorflow model who mask logits of illegal actions.