How Do Genetic Algorithms Work? [video]

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Genetic algorithms are in the class of evolutionary algorithms that build on the principle of “survival of the fittest”. By recombining the best solutions of a population and every now and then mutating them, one can solve remarkably difficult problems that would otherwise be hopelessly difficult to write programs for.

One of the first works of genetic algorithms, “Adaptation in Natural and Artificial Systems” by John H. Holland:
https://mitpress.mit.edu/books/adaptation-natural-and-artificial-systems

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A parallel genetic algorithm for the Mona Lisa problem:
https://cg.tuwien.ac.at/~zsolnai/gfx/mona_lisa_parallel_genetic_algorithm/

A parallel, console genetic algorithm for the 0-1 knapsack problem:
https://cg.tuwien.ac.at/~zsolnai/gfx/knapsack_genetic/

John Henry Holland, the father of genetic algorithms:
https://en.wikipedia.org/wiki/John_Henry_Holland

Try this out, it’s really fun! – http://boxcar2d.com/

The Blind Watchmaker by Richard Dawkins (note: if you buy through here, I get a very small commission):
http://amzn.to/1Lfkhac

The thumbnail background image was created by Karen Roe (CC BY 2.0) – https://flic.kr/p/ezxAbk

Subscribe if you would like to see more of these! – http://www.youtube.com/subscription_center?add_user=keeroyz

Splash screen/thumbnail design: Felícia Fehér – http://felicia.hu/

Károly Zsolnai-Fehér’s links:
Patreon ? https://www.patreon.com/TwoMinutePapers
Facebook ? https://www.facebook.com/TwoMinutePapers/
Twitter ? https://twitter.com/karoly_zsolnai
Web ? https://cg.tuwien.ac.at/~zsolnai/

View the original article here

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