Genetic Algorithms Produce Winning StarCraft II Build Order (2010)

Re:Genetic Algorithms Produce Winning StarCraft II Build Ord... by marcosdumay on Monday March 24, 2014 @06:09PM (#7461997)

Well, crossover is extremely powerfull and makes genetic algorithms very genereic. You are right that it's probably overkill for most problems we solve with computers, but only because we solve very simple problems nowadays.

Anyway, my experience with automatic programming is completely oposite to yours, and in line with comicjk. I've always had better results with GA than with hill climbing* or simulated annealing. I have the same experience for resource scheduling. Of course, your experience will vary a lot depending on the data you want to fit/schedule.

Also, nothing is stopping you from including hill climbing as a kind of mutation...

* Last time I used it, I didn't even have a well behaved gradient to climb, it was zero at a huge number of places, and I knew it beforehand. Automatic programming applies to all kinds of crazy domains.

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Re:Genetic Algorithms Produce Winning StarCraft II Build Ord... by jules on Monday March 24, 2014 @06:39PM (#7462231)

You should publish a paper on the problem you solved with GA. It will be a huge breakthrough, since so far here is only 1 problem known to work better with GAs than hill climbing, and it's a toy problem specifically crafted for this purpose.

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Re:Genetic Algorithms Produce Winning StarCraft II Build Ord... by marcosdumay on Wednesday March 26, 2014 @10:40AM (#7473684)

I'm not very inclined to share it.

I was trying to fit a potential field, that I knew consisted of a map of 12 dimensions into 1. I could approximate it pointwise, but only with a very slow procedure, and needed both a faster one and a derivative.

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