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[STEAM] “Superhuman” Go AIs still have trouble defending against these simple exploits

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/ Man vs. machine in a sea of stones. (credit: Getty Images)

[/url] In the ancient ********* game of Go, state-of-the-art artificial intelligence has generally been able to defeat the best human players
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. But in the last few years, researchers have
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that
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. By using unorthodox "cyclic" strategies—ones that even a beginning human player could detect and defeat—a crafty human can often exploit gaps in a top-level AI's strategy and fool the algorithm into a loss.

Researchers at MIT and
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wanted to see if they could improve this "worst case" performance in otherwise "superhuman" AI Go algorithms, testing a trio of methods to harden the top-level
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's defenses against adversarial attacks. The results show that creating truly robust, unexploitable AIs may be difficult, even in areas as tightly controlled as board games.

Three ******* strategies
In the pre-print paper
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, the researchers aim to create a Go AI that is truly "robust" against any and all attacks. That means an algorithm that can't be fooled into "game-losing blunders that a human would not commit," but also one that would require any competing AI algorithm to spend significant computing resources to defeat it. Ideally, a robust algorithm should also be able to overcome potential exploits by using additional computing resources when confronted with unfamiliar situations.

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