Developing StarCraft 2 Build Orders With Genetic Algorithms
 

Jamie recommends a blog post from software engineer Louis Brandy explaining how using genetic algorithms to evaluate build orders in StarCraft 2 has led to some surprisingly powerful results. Quoting: "One of the reasons build-order optimization is so important is that you can discover openings that 'hard-counter' other openings. If I can get an army of N size into your base when you do opening X, you will always lose. ... a genetic algorithm is a type of optimization algorithm that tries to find optimal solutions using a method analogous to biologic evolution (to be specific: descent with modification & natural selection). Put simply, you take a 'population' of initial build orders, evaluate them for fitness, and modify the population according to each element’s fitness. In other words, have the most successful reproduce. The program’s input is simply the desired game state. In practice, this means 'make N units' to determine some rush build order (but it also allows for other types of builds, like make N workers with some defensive structures and a small army)."
Read more of this story at Slashdot.
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