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Multi-Agent System for Metrology for Factory of the Future (Met4FoF) Code

This is supported by European Metrology Programme for Innovation and Research (EMPIR) under the project Metrology for the Factory of the Future (Met4FoF), project number 17IND12. (https://www.ptb.de/empir2018/met4fof/home/)

About

  • How can metrological input be incorporated into an agent-based system for addressing uncertainty of machine learning in future manufacturing?
  • Includes agent-based simulation and implementation
  • Readthedocs documentation is available at (https://agentmet4fof.readthedocs.io)

Get started

First clone the repository to your local machine as described here. To get started with your present Anaconda installation just go to Anaconda prompt, navigate to your local clone

cd /your/local/folder/agentMet4FoF

and execute

conda env create --file environment.yml

This will create an Anaconda virtual environment with all dependencies satisfied. If you don't have Anaconda installed already follow this guide first, then create the virtual environment as stated above and then proceed.

Alternatively, for non-conda environments, you can install the dependencies using pip

pip install -r requirements.txt

First take a look at the tutorials and examples or start hacking if you already are familiar with agentMET4FOF and want to customize your agents' network.

Alternatively, watch the tutorial webinar here

Updates

  • Implemented base class AgentMET4FOF with built-in agent classes DataStreamAgent, MonitorAgent
  • Implemented class AgentNetwork to start or connect to a agent server
  • Implemented with ZEMA prognosis of Electromechanical cylinder data set as use case DOI
  • Implemented interactive web application with user interface

Screenshot of web visualization

Web Screenshot

Note

  • In the event of agents not terminating cleanly, run

    taskkill /f /im python.exe /t

    in Windows Command Prompt to terminate all background python processes.

Project links

Key dates

PyPI data
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  • Released:
Newer release available (0.13.4)

2 maintainers

PyPI data
Data sourced directly from PyPI's database.
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Credits

Author: Bang Xiang Yong, Björn Ludwig, Haris Lulic

License

GNU Lesser General Public License v3 (LGPLv3)

Requires

Python >=3

Tags

uncertainty metrology MAS agent-based agents

Classifiers

Report project as malware

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0.13.4

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0.13.3

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0.13.2

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0.13.1

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0.2.0.dev1

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This release

0.1.1 This release

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