Are they ready? Oliver Berg/dpa/Alamy Live News

StarCraft players are safe – but not for long. The machines that made short work of chess, Scrabble and Go are beginning to set their sights on the venerable video game. And while the inherent complexity of most video games makes them a much harder target for AI than board games, two new projects aim to show they are far from invulnerable.

One is a training ground for artificial intelligences targeting StarCraft, opened today by the game’s creator, Blizzard Entertainment, in collaboration with Google’s AI company DeepMind. The other is an AI being developed by researchers in Denmark whose approach stands the first good chance of beating a human at the game. But this isn’t just about video game supremacy: beating StarCraft could drive forward the entire field of artificial intelligence.

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As part of their training ground, DeepMind and Blizzard released a suite of tools designed to make it easier for researchers to develop AI players. They also promised to release hundreds of thousands of videos showing real games for them to train on.


The new foray comes hot on the heels of DeepMind’s success at cracking Go. Earlier this year, the company’s specialist AI, AlphaGo, defeated the world’s number one ranked player Ke Jie 3 – 0, demonstrating for the first time an AI with superhuman mastery of the game. To get that good, AlphaGo analysed and learned from millions of human moves, and played thousands of games against itself.

Human dominance

But StarCraft is a far harder target. Pit artificial intelligence against a human in the game and it crumbles. Even an amateur can beat the best artificial players. “If there was a way that you could record how much processing a human playing StarCraft optimally does, it would be astonishing,” says Georgios Yannakakis at the University of Malta.

StarCraft involves building armies and infrastructure to battle opponents over a large, virtual terrain. The main reason why the game is so difficult for AI is the sheer number of possible ways a match can play out.

It is estimated that there are 101685 possible configurations for each match. In comparison, Go has around 10170. You could count every proton in the universe, and add every second that has elapsed since the big bang, and you still wouldn’t be anywhere near the number of possible StarCraft positions.

What’s more, unlike board games, where moves are taken in turn, players play simultaneously and in real time. And players often can’t see exactly what their opponents are up to, so decisions must be made based on incomplete information.

All this means that you can’t just use brute force to find the best ways to play the game. So instead of working out what the optimal move is, players need strategies to guide them – and intuition.

Learning from the best

Now Sebastian Risi and his colleague Niels Justesen at the IT University of Copenhagen, Denmark, have started to apply the AlphaGo approach to StarCraft. So far, they have trained their AI on around 630,000 moves extracted from over 2000 games involving some of the best human StarCraft players. This has allowed it to slowly learn to predict what a successful human would do in a given state of the game, so that it can do a similar thing when faced with a similar choice.

At the moment, Risi and Justesen’s approach can even still be beaten by some other StarCraft-playing AIs. However, these have human strategies hard-coded into them, meaning that once a human opponent finds a vulnerability in their strategy, they will beat them handily from then on – the AI can’t adapt.

Risi and Justesen’s AI is the first to use deep neural networks, a computer technique that mimics neurons in the brain, to learn from human StarCraft games. This means their AI will learn strategies for itself, which they hope will eventually lead it to surpass the competition – and it well may, given that the same approach led AlphaGo to dominance.

Over the next few months, it will start playing games against itself to further hone its skills – maybe within the DeepMind dojo. “We can’t wait to try it,” says Risi. Their work will be presented at the Computational Intelligence in Games conference at the end of this month.

DeepMind isn’t the only company trying to train up StarCraft-playing AI – yesterday, Facebook released its own data set. There’s more to all this than just video game accolades. “StarCraft is closer to the real world than games like Go,” says Risi.

This means that cracking StarCraft could even speed up general progress in artificial intelligence, as mastering the game requires a sophisticated combination of memory, strategy and planning. “The richness of the game means it is a useful bridge to the real world,” says Oriol Vinyals at DeepMind.