DTSimioRL
Digital Twin Reinforcement Learning algorithm for Simio
How to use
Step0 : step 0 for scenario 1
Step02 : step 0 for scenario 2
Step1 : step 1 for scenario 1
Step12 : step 1 for scenario 2
Step2 : step 2 for scenario 1
Step22 : step 2 for scenario 2
Step3 : step 3 for scenario 1
Step32 : step 3 for scenario 2
For both scenarios:
step 0 creates Qtable
step 1 computes a random action for training phase
step 2 calculates the Q table
step 3 returns the action of the max Q for using (testing) phase
Corresponding Simio files are in the repository.
Team
Contributing
This project is open-source, and contributions are welcome. If you want to contribute, you can do so by forking the project and submitting a pull request with your changes. You can also report bugs or suggest new features by creating an issue on the project's Github page.
License
This project is licensed under the MIT License. You are free to use, modify, and distribute the code under the terms of this license. See the LICENSE file for more information.