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January 31, 2009

Recreating the Mona Lisa

Swedish programmer Roger Alsing has published an example of genetic programming which evolves a set of randomly placed polygons into an image of the Mona Lisa. Alsing's algorithm starts with the set of random polygons on a black background, then iteratively tests and adjusts them against a final image. After about a million iterations, the polygons are rearranged to resemble the final image. There is some controversy as to whether this can be called genetic programming, or represents a variation of known procedures such as the hillclimbing algorithm. In any case, the results are impressive.

Read Roger Alsing's response to questions about his program on his FAQ page. Commentary on the program can be read on the Pharyngula and io9 blogs.

Posted by BlogAuthor1 at January 31, 2009 10:28 PM
category: Evolutionary Computation


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