Computational Model Library

MGA - Minimal Genetic Algorithm (1.0.0)

Genetic algorithms try to solve a computational problem following some principles of organic evolution. This model has educational purposes; it can give us an answer to the simple arithmetic problem on how to find the highest natural number composed by a given number of digits. We approach the task using a genetic algorithm, where the candidate solutions to the problem are represented by agents, that in logo programming environment are usually known as “turtles”.

MinGA_GUI.png

Release Notes

See the info-tab attached to the code file

Associated Publications

This release is out-of-date. The latest version is 1.1.0

MGA - Minimal Genetic Algorithm 1.0.0

Submitted by Cosimo Leuci Published Sep 03, 2019 Last modified Sep 19, 2020
education arithmetic genetic algorithm NetLogo

Genetic algorithms try to solve a computational problem following some principles of organic evolution. This model has educational purposes; it can give us an answer to the simple arithmetic problem on how to find the highest natural number composed by a given number of digits. We approach the task using a genetic algorithm, where the candidate solutions to the problem are represented by agents, that in logo programming environment are usually known as “turtles”.

Release Notes

See the info-tab attached to the code file

Cite this Model

Cosimo Leuci (2019, September 03). “MGA - Minimal Genetic Algorithm” (Version 1.0.0). CoMSES Computational Model Library. Retrieved from: https://doi.org/10.25937/7kta-pf44

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Contributors
Cosimo Leuci
External Repository
github.com/cleuci/Minimal-Genetic-Algorithm
DOI

10.25937/7kta-pf44

Model Version
1.0.0
License
CC-BY-NC-SA-4.0
Programming Language
NetLogo
Software Framework
NetLogo
Operating System
Operating System Independent
Publish Date
Tuesday, September 03, 2019
Last Updated
Monday, January 20, 2020
Downloads 175
Peer Reviewed
Open Code Badge
Version Submitter First published Last modified Status
1.1.0 Cosimo Leuci Thu Jan 30 08:42:08 2020 Tue Oct 24 11:35:49 2023 Published Peer Reviewed https://doi.org/10.25937/db7w-zt41
1.0.0 Cosimo Leuci Tue Sep 3 07:52:29 2019 Mon Jan 20 05:46:29 2020 Published Peer Reviewed https://doi.org/10.25937/7kta-pf44

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