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The Tale Of The Ultimate Starcraft AI

The techno-chaps over at Ars Technica have posted an interesting story about the development of the ultimate Starcraft AI. Written by student Haomiao Huang, it’s the story of the “Berkeley Overmind”, which recently beat Starcraft pros a former Starcraft pro in head-to-head matches (although it is a way off beating the real current masters, it seems). Here’s a snippet: “In theory, a computer should be great at controlling many units simultaneously, since it’s not limited by human speeds. Indeed, there is a common misconception that because StarCraft is real-time, it must be game of reflexes. But while speed is useful and important, it is no substitute for knowing the right thing to do… To handle these issues and limit computational overhead, our agent uses artificial potential fields for unit movement. The potential field controller generates virtual forces that push the mutalisks around, balancing attractive forces on targets with repulsive forces on threats. Summing up the forces acting on a mutalisk gives a direction to fly, resulting in a simple but robust control scheme.”

A useful read for those of you interested in the subtleties of game AI, with some illustrative videos. Go read!

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Jim Rossignol

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