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I've looked at random forests before, but only briefly, and only because I saw on Wikipedia that they are like the state of the art in machine learning classification algorithms. :-P The other classification system I've always wanted to tinker with was Support Vector Machines, which I learned about in school and seemed really cool/versatile.

My main efforts to top KNN have been clustering algorithms, mainly a dynamic-ish k-means and one based on "quality threshold" clustering. I managed to get hybrid systems (meaning they use KNN until they have some clusters) on par with my KNN targeting, but getting the same accuracy at a fraction of the speed wasn't useful.

KNN really is fast as heck and just seems perfectly suited to the Robocode scenario. But Pris is pretty damn impressive with the neural nets and I'm sure someone could do better.