Genetic programming has evolved over the last decade with computer programmers using biological evolution as an inspiration for how computer programs can respond to an environment (set of values that make up a solution).
The idea is that a program can somehow evaluate the "goodness of fit" of the solution it comes up with in a particular environment and adjust some elements of its operation to improve that fit.
A Slashdot article today showcases a blogger who wrote a genetic program that uses an arrangement of polygons and was set to compare the arrangement with an image of the Mona Lisa. Having evaluated whether the arrangement is an improvement (is closer to what Mona Lisa looks like) the program adjusts the "DNA" (elements that it is using to create the approximation of the image) and tries again.
The resultant series of images is quite impressive.
Log Insight: Aliasing Feature - I covered the datastore ID to name aliasing feature in Log Insight 4.0, but under the covers is really a more generic aliasing feature that has not been ...
1 week ago