How Genetic Algorithms Work | Two Minute Papers 🧬

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 mentioned book is called "The Blind Watchmaker" by Richard Dawkins.

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