Nano Version Control and "Robots of Robots"- Data Driven, Regenerative Production Code

Lukasz MacHowski, Tshilidzi Marwala

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The Corona pandemic highlights the need for sustainable production systems using automation. Traditional automation is fragile and hard to get right. This method converts one hard problem of producing sustainable production code into three simpler problems: data, patterns and working prototypes. By using agent-based simulation and NanoVC repos for agent arbitration, we create a simulated environment for the approach. Patterns developed by people are used to transform working prototypes into templates where data is fed through to create the robots that create the production code. Having two layers of robots allow early implementation choices to be replaced. Robot of Robots encode a legacy of the person that designed them, thus reducing the fragility of the production code.

Original languageEnglish
Title of host publicationProceedings - 2021 International Conference on Computational Science and Computational Intelligence, CSCI 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1938-1943
Number of pages6
ISBN (Electronic)9781665458412
DOIs
Publication statusPublished - 2021
Event2021 International Conference on Computational Science and Computational Intelligence, CSCI 2021 - Las Vegas, United States
Duration: 15 Dec 202117 Dec 2021

Publication series

NameProceedings - 2021 International Conference on Computational Science and Computational Intelligence, CSCI 2021

Conference

Conference2021 International Conference on Computational Science and Computational Intelligence, CSCI 2021
Country/TerritoryUnited States
CityLas Vegas
Period15/12/2117/12/21

Keywords

  • agent-based-modelling
  • nano version control

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Safety, Risk, Reliability and Quality

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