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Genetic Algorithms (GA) are a fun and interesting way to, in my opinion, have a directed (heuristic) brute force method rooted in biological functions. While they are not an end all-be all solution I think their solution space can provide interesting answers for interesting applications. The gist of GAs is to throw possible solutions at the wall, determine which are closer to your goal, drop those that are not, and create new solutions from those closest to the goal. Simple enough, right?

Posted by macosxnerd101  |   Submitted: May 02 2013 / 08:34

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