agentMET4FOF


NameagentMET4FOF JSON
Version 0.6.0 PyPI version JSON
download
home_pagehttps://github.com/bangxiangyong/agentMET4FOF
SummaryA software package for the integration of metrological input into an agent-based system for the consideration of measurement uncertainty in current industrial manufacturing processes.
upload_time2021-02-23 17:08:48
maintainer
docs_urlNone
authorBang Xiang Yong, Björn Ludwig, Anupam Prasad Vedurmudi, Maximilian Gruber, Haris Lulic
requires_python>=3.8
license
keywords uncertainty metrology mas agent-based agents
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            <p align="center">
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<h1 align="center">Multi-Agent System for IIoT</h1>

<p align="justify">
agentMET4FOF is an implementation of a multi-agent system for agent-based 
analysis and processing of both static data sets and data streams with IIoT 
applications in mind. More on the motivation that drives the project can be found
in the section <a href="#about">About</a>.
</p>

## Table of content

- [💫 Quickstart](#quickstart)
- [💬 About](#about)
- [📈 The agentMET4FOF dashboard](#the-agentmet4fof-dashboard)
- [📖 Documentation and video tutorials](#documentation-and-video-tutorials)
- [💻 Installation](#installation)
- [💨 Coming soon](#coming-soon)
- [💎 Acknowledgement](#acknowledgement)
- [⚠ Disclaimer](#disclaimer)
- [© License](#license)

## 💫Quickstart

agentMET4FOF comes bundled with some tutorials to get you started as quick as
possible. In your Python console execute the following to run the first tutorial.

```python
>>> from agentMET4FOF_tutorials.tutorial_1_generator_agent import demonstrate_generator_agent_use
>>> generator_agent_network = demonstrate_generator_agent_use()
```

```shell
Starting NameServer...
Broadcast server running on 0.0.0.0:9091
NS running on 127.0.0.1:3333 (127.0.0.1)
URI = PYRO:Pyro.NameServer@127.0.0.1:3333

--------------------------------------------------------------
|                                                            |
| Your agent network is starting up. Open your browser and   |
| visit the agentMET4FOF dashboard on http://127.0.0.1:8050/ |
|                                                            |
--------------------------------------------------------------

INFO [2021-02-05 18:12:52.277759] (SineGeneratorAgent_1): INITIALIZED
INFO [2021-02-05 18:12:52.302862] (MonitorAgent_1): INITIALIZED
[2021-02-05 18:12:52.324078] (SineGeneratorAgent_1): Connected output module: MonitorAgent_1
SET STATE:   Running
[...]
```
```python
>>> generator_agent_network.shutdown()
0
NS shut down.
```


## 💬About

<p align="justify">
Sensor deployments in industrial applications usually form networks in all sorts of
environments. This requires a flexible framework for the implementation of the
corresponding data analysis. An excellent way to represent such networks is a
multi-agent system (MAS), where independent software modules (agents) encapsulate
properties and functionalities. agentMET4FOF is an interactive and flexible open-source
implementation of such a MAS. The software engineering process is driven by several
industry-oriented use cases with the aim of impacting on IIoT applications. This leads
to a framework that is specialized in representing heterogeneous sensor networks.
</p>
<p align="justify">
A special emphasize is put on supporting metrological treatment of sensor streaming
data. This includes the consideration of measurement uncertainties during data analysis
and processing as well as propagating metadata alongside the data itself.
</p>
<p align="justify">
One of the many questions that drive us in the project is:
</p>
<p align="justify">
  <cite>
  How can metrological input be incorporated into an agent-based system for addressing
  uncertainty of machine learning in future manufacturing?
  </cite>
</p>

## 📈The agentMET4FOF dashboard

agentMET4FOF comes bundled with our so called _dashboard_. It is an optional component
of every agent network and provides a web browser based view. You can
observe the state of your agents, modify the connections between them and even add
more pre-made agents to your network all during run-time. The address to your
dashboard is printed to the console on every launch of an agent network.

The following image is close to what you will find in your browser on execution of
tutorial 2. For details on the tutorials visit our [video tutorial series](#video-tutorial-series).

![Web Screenshot](https://raw.githubusercontent.com/Met4FoF/agentMET4FOF/develop/docs/screenshot_met4fof.png)

## 📖Documentation and video tutorials

Extended
[documentation can be found on ReadTheDocs](https://agentmet4fof.readthedocs.io).

### Video tutorial series

Additionally, we provide some [video tutorials based on agentMET4FOF 0.4.1 on the project homepage](https://www.ptb.de/empir2018/met4fof/information-communication/video-portal/)
in the section _Tutorials for the multi-agent system agentMET4FOF_. 
You can self-register on the linked page and get started immediately. The video series
begins with our motivation for creating agentMET4FOF, guide you through the
installation of Python and other recommended software until you execute the tutorials
on your machine.

### Live online tutorial during early development

In an early development stage we held a live online tutorial based on 
[agentMET4FOF 0.1.0](https://github.com/Met4FoF/agentMET4FOF/releases/0.1.0/) 
which you can [download](https://github.com/Met4FoF/agentMET4FOF/releases/download/0.1.0/Met4FoF.MAS.webinar.mp4).

If questions arise, or you feel something is missing, reach out to [us](https://github.com/Met4FoF/agentMET4FOF/graphs/contributors).

## 💻Installation

The installation of agentMET4FOF is as straightforward as the Python 
ecosystem suggests. In the [video tutorials series](#video-tutorial-series)
we guide you through every step until you have agentMET4FOF running on 
your machine. Besides that we have more details in the [installation 
section of the docs](https://agentmet4fof.readthedocs.io/en/latest/INSTALL.html).

## 💨Coming soon

- Dockerize agentMET4FOF
- Improve handling of metadata
- Further improve plotting

For a comprehensive overview of current development activities and upcoming tasks,
take a look at the [project board](https://github.com/Met4FoF/agentMET4FOF/projects/1),
[issues](https://github.com/Met4FoF/agentMET4FOF/issues) and
[pull requests](https://github.com/Met4FoF/agentMET4FOF/pulls).

## 💎Acknowledgement

This work was part of the Joint Research Project [Metrology for the Factory of the Future (Met4FoF), project number 17IND12](https://www.ptb.de/empir2018/met4fof/home/)
of the European Metrology Programme for Innovation and Research (EMPIR). The [EMPIR](http://msu.euramet.org)
is jointly funded by the EMPIR participating countries within EURAMET and the European 
Union.

## ⚠Disclaimer

This software is developed as a joint effort of several project partners namely:

- [Institute for Manufacturing of the University of Cambridge (IfM)](https://www.ifm.eng.cam.ac.uk/)
- [Physikalisch-Technische Bundesanstalt (PTB)](https://www.ptb.de/)
- [Van Swinden Laboratory (VSL)](https://www.vsl.nl/en/)
- [National Physics Laboratory (NPL)](https://www.npl.co.uk/)

under the lead of IfM. The software is made available "as is" free of cost. The 
authors and their institutions assume no responsibility whatsoever for its use by 
other parties, and makes no guarantees, expressed or implied, about its quality, 
reliability, safety, suitability or any other characteristic. In no event will the 
authors be liable for any direct, indirect or consequential damage arising in 
connection with the use of this software.

## ©License

agentMET4FOF is distributed under the [LGPLv3 license](https://github.com/Met4FoF/agentMET4FOF/blob/develop/license.md).




            

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More on the motivation that drives the project can be found\nin the section <a href=\"#about\">About</a>.\n</p>\n\n## Table of content\n\n- [\ud83d\udcab Quickstart](#quickstart)\n- [\ud83d\udcac About](#about)\n- [\ud83d\udcc8 The agentMET4FOF dashboard](#the-agentmet4fof-dashboard)\n- [\ud83d\udcd6 Documentation and video tutorials](#documentation-and-video-tutorials)\n- [\ud83d\udcbb Installation](#installation)\n- [\ud83d\udca8 Coming soon](#coming-soon)\n- [\ud83d\udc8e Acknowledgement](#acknowledgement)\n- [\u26a0 Disclaimer](#disclaimer)\n- [\u00a9 License](#license)\n\n## \ud83d\udcabQuickstart\n\nagentMET4FOF comes bundled with some tutorials to get you started as quick as\npossible. In your Python console execute the following to run the first tutorial.\n\n```python\n>>> from agentMET4FOF_tutorials.tutorial_1_generator_agent import demonstrate_generator_agent_use\n>>> generator_agent_network = demonstrate_generator_agent_use()\n```\n\n```shell\nStarting NameServer...\nBroadcast server running on 0.0.0.0:9091\nNS running on 127.0.0.1:3333 (127.0.0.1)\nURI = PYRO:Pyro.NameServer@127.0.0.1:3333\n\n--------------------------------------------------------------\n|                                                            |\n| Your agent network is starting up. Open your browser and   |\n| visit the agentMET4FOF dashboard on http://127.0.0.1:8050/ |\n|                                                            |\n--------------------------------------------------------------\n\nINFO [2021-02-05 18:12:52.277759] (SineGeneratorAgent_1): INITIALIZED\nINFO [2021-02-05 18:12:52.302862] (MonitorAgent_1): INITIALIZED\n[2021-02-05 18:12:52.324078] (SineGeneratorAgent_1): Connected output module: MonitorAgent_1\nSET STATE:   Running\n[...]\n```\n```python\n>>> generator_agent_network.shutdown()\n0\nNS shut down.\n```\n\n\n## \ud83d\udcacAbout\n\n<p align=\"justify\">\nSensor deployments in industrial applications usually form networks in all sorts of\nenvironments. This requires a flexible framework for the implementation of the\ncorresponding data analysis. An excellent way to represent such networks is a\nmulti-agent system (MAS), where independent software modules (agents) encapsulate\nproperties and functionalities. agentMET4FOF is an interactive and flexible open-source\nimplementation of such a MAS. The software engineering process is driven by several\nindustry-oriented use cases with the aim of impacting on IIoT applications. This leads\nto a framework that is specialized in representing heterogeneous sensor networks.\n</p>\n<p align=\"justify\">\nA special emphasize is put on supporting metrological treatment of sensor streaming\ndata. This includes the consideration of measurement uncertainties during data analysis\nand processing as well as propagating metadata alongside the data itself.\n</p>\n<p align=\"justify\">\nOne of the many questions that drive us in the project is:\n</p>\n<p align=\"justify\">\n  <cite>\n  How can metrological input be incorporated into an agent-based system for addressing\n  uncertainty of machine learning in future manufacturing?\n  </cite>\n</p>\n\n## \ud83d\udcc8The agentMET4FOF dashboard\n\nagentMET4FOF comes bundled with our so called _dashboard_. It is an optional component\nof every agent network and provides a web browser based view. You can\nobserve the state of your agents, modify the connections between them and even add\nmore pre-made agents to your network all during run-time. The address to your\ndashboard is printed to the console on every launch of an agent network.\n\nThe following image is close to what you will find in your browser on execution of\ntutorial 2. For details on the tutorials visit our [video tutorial series](#video-tutorial-series).\n\n![Web Screenshot](https://raw.githubusercontent.com/Met4FoF/agentMET4FOF/develop/docs/screenshot_met4fof.png)\n\n## \ud83d\udcd6Documentation and video tutorials\n\nExtended\n[documentation can be found on ReadTheDocs](https://agentmet4fof.readthedocs.io).\n\n### Video tutorial series\n\nAdditionally, we provide some [video tutorials based on agentMET4FOF 0.4.1 on the project homepage](https://www.ptb.de/empir2018/met4fof/information-communication/video-portal/)\nin the section _Tutorials for the multi-agent system agentMET4FOF_. \nYou can self-register on the linked page and get started immediately. The video series\nbegins with our motivation for creating agentMET4FOF, guide you through the\ninstallation of Python and other recommended software until you execute the tutorials\non your machine.\n\n### Live online tutorial during early development\n\nIn an early development stage we held a live online tutorial based on \n[agentMET4FOF 0.1.0](https://github.com/Met4FoF/agentMET4FOF/releases/0.1.0/) \nwhich you can [download](https://github.com/Met4FoF/agentMET4FOF/releases/download/0.1.0/Met4FoF.MAS.webinar.mp4).\n\nIf questions arise, or you feel something is missing, reach out to [us](https://github.com/Met4FoF/agentMET4FOF/graphs/contributors).\n\n## \ud83d\udcbbInstallation\n\nThe installation of agentMET4FOF is as straightforward as the Python \necosystem suggests. In the [video tutorials series](#video-tutorial-series)\nwe guide you through every step until you have agentMET4FOF running on \nyour machine. 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