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9.10: Genetic Algorithm: Continuous Evolutionary System - The Nature of Code

In this video, I apply the Genetic Algorithm to an "Ecosystem Simulation", a system which models biological life more closely, where elements live and die continuously evolving over time. Code: https://thecodingtrain.com/tracks/the-nature-of-code-2/noc/9-genetic-algorithms/10-continuous-evolutionary-systems

🕹️ p5.js Web Editor Sketch: https://editor.p5js.org/natureofcode/sketches/1HDlp_tKF

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References:
🔗 Nature of Code: https://nature-of-code-2nd-edition.netlify.app/

Related Coding Challenges:
🚂 https://youtu.be/bGz7mv2vD6g
🚂 https://youtu.be/flxOkx0yLrY

Timestamps:
0:00 Welcome to one more video about genetic algorithms!
0:56 Comparison to real world
2:11 Explain system of "Bloops"
4:42 How does genetic information get passed on?
6:23 Things to think about
7:17 No fitness function -- survival of the "survivors"
7:41 Outro

Editing by Mathieu Blanchette
Animations by Jason Heglund
Music from Epidemic Sound

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🔗 p5.js: https://p5js.org
🔗 p5.js Web Editor: https://editor.p5js.org/
🔗 Processing: https://processing.org

📄 Code of Conduct: https://github.com/CodingTrain/Code-of-Conduct

This description was auto-generated. If you see a problem, please open an issue: https://github.com/CodingTrain/thecodingtrain.com/issues/new

#geneticalgorithms #ecosystemsimulation #p5js

Видео 9.10: Genetic Algorithm: Continuous Evolutionary System - The Nature of Code канала The Coding Train
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12 августа 2016 г. 1:49:58
00:08:00
Яндекс.Метрика