My issue with GA is that they are definitely the sexiest&#x2F;best known evolutionary algorithm in their class, so they get used for a lot of things that they&#x27;re not really designed for. GA work best if you have lots of discrete parameters that combine in weird ways to determine fitness (you know, like DNA). I&#x27;m a structural engineer, and most search problems I run into have a smaller number of continuously valued parameters (like the locations of the joints in the car in the video). GA tends to try to swap parameters between the fittest of the previous generation, instead of looking in the area between those individuals.