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Two Minute Papers: How Do Genetic Algorithms Work? #32 •

In this AI video ...

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 on genetic algorithms is “Adaptation in Natural and Artificial Systems” by John H. Holland.

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 – if you still have Adobe Flash, it’s really fun! – http://boxcar2d.com

The mentioned book is called “The Blind Watchmaker” by Richard Dawkins.

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

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

YouTube Source for this AI/Deep Learning/Research Video

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