mlpro-mpps 1.0.1

MLPro-MPPS - A Customizable Multi-Purpose Production System in Python

MLPro-MPPS - A Customizable Multi-Purpose Production Systems in Python

MLPro-MPPS provides functionalities to design and develop customizable multi-purpose production systems in Python. This framework is integrated with MLPro (https://mlpro.readthedocs.io) and inherits several basic functionalities from MLPro. The user can design a simulation of a production system from the lowest component level (sensors and actuators) until the combination of them in form of MPPS. The other possibility is to use the ready-to-use components in the pool of objects. Moreover, since MLPro-MPPS is compatible with MLPro, it is possible to utilize MLPro-MPPS as an environment in MLPro-RL, as a game board in MLPro-GT, or as a state transition function in a MLPro-BF-Systems. Hence, MLPro-MPPS is reusable and powerful.

Getting Started

To get started with MLPro-MPPS, you can begin with the following tasks:

Installation from PyPI

............ (Available soon)

Installation from Anaconda

............ (Available soon)

Dependencies

Please read requirements.txt

First Steps

After installing MLPro-MPPS and its dependencies, we suggest starting with the ready-to-run examples:

1. HOWTO 001 - SETTING UP COMPONENTS AND MODULES
2. HOWTO 002 - SETTING UP MPPS
3. HOWTO 003 - MPPS IN REINFORCEMENT LEARNING
4. HOWTO 004 - MPPS IN GAME THEORY

Additionally, the class diagram of the basic function is available in this directory. The ready-to-use components and MPPS samples can be found in this directory.

Key Features and Functionalities

What are the elements? How to setup components and MPPS? Integrations to MLPro? (MPPS as RL env, GT game board, etc.) ............

Development

• Consequent object-oriented design and programming (OOD/OOP)
• Quality assurance by test-driven development
• Hosted and managed on GitHub
• Agile CI/CD approach with automated test and deployment
• Clean code paradigma

Citing MLPro-MPPS

......

Project and Team

Project MLPro-MPPS was started in 2022 by the Group for Automation Technology and Learning Systems at the South Westphalia University of Applied Sciences, Germany.

MLPro is currently designed and developed by Steve Yuwono, Marlon Löppenberg, Detlef Arend and further contributors.

How to contribute

If you want to contribute, please read CONTRIBUTING.md