The importance of genetic algorithms in computer art

It is easy to produce simple algorithms that will give interesting images but, as in this case, the number of possible images is so huge that the best way is to let the computer generate them randomly. Unfortunately trying to get a good image in this way is like waiting for the proverbial ape to produce a Shakespeare sonnet by clicking randomly on a keyboard. To accellerate the process of finding these interesting images, the genetic algorithm is fundamental. This method has been explored from computer artists like William Latham ,Roman Verosko and Karl Sims (in fact the basic idea behind the images in the gallery was described from K.Sims at Siggraph 91). The idea behind genetic algorithms is very simple In the end the essential ingredients are: In this way the artist will drive the evolution of new images without having to know any detail on the maths behind.

This is also called Evolutionary Art.The artist applies the principles of Darwinian Evolution to breed genetic algorithms from gene banks.
The evolutionary art of Steven Rooke explains in details how this technique is applied from an evolutionary artist.

This idea is used also to create images based on the preferences of Internet surfers like in this gallery of random art by Andrey Bauer where you can find also a good description of his method in How random art works.(His method,I think,is exactly the one described in the Siggraph paper).

You can even experiment with genetic art yourself in this applet where IFS fractals are used to produce the images.

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