Humans have been bested by a computer in yet another game once considered too difficult for artificial intelligence to master.
Over the past three weeks, an AI poker bot called Libratus has played thousands of games of heads-up, no-limit Texas hold’em against a cadre of top professional players at Rivers Casino in Pittsburgh. And it beat them all.
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Our own Will Knight recently explained why victory for Libratus, which was built by a pair of researchers at Carnegie Mellon University, would be such a big deal:
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Poker requires reasoning and intelligence that has proven difficult for machines to imitate. It is fundamentally different from checkers, chess, or Go, because an opponent’s hand remains hidden from view during play. In games of “imperfect information,” it is enormously complicated to figure out the ideal strategy given every possible approach your opponent may be taking.
In heads-up, no-limit Texas hold’em, then, it’s virtually impossible, for there is no single correct play. Instead, the AI must use game theory to calculate optimal plays given the uncertainties.
In the end, it wasn’t even close: Libratus made off with $1.8 million in chips, while all four of the pros ended up with a deficit. Artificial intelligence has never beaten top players at a game so lacking in information as no-limit Texas hold’em. Like DeepMind’s Go victory before it, then, the win is a seminal moment for the machine learning community.
But what was it like for the humans to play against? “It’s slightly demoralizing,” Jason Les, one of the professionals, told the Guardian. “If you play a human and lose, you can stop, take a break. Here we have to show up to take a beating every day for 11 hours a day. It’s a real different emotional experience when you’re not used to losing that often.”
Daniel McAulay, another professional, explained to Wired that the AI’s ability to hold different plays in its memory made it stand apart from human contenders. “It splits its bets into three, four, five different sizes,” he explained. “No human has the ability to do that.” Still, don’t feel too badly for the vanquished humans: despite losing, they’re divvying up $200,000 between themselves based on how well they did during the tournament.
For the AI, though, this is just the start. Having proven that it’s possible to beat the professionals at their own game, there is now a very clear next challenge to chew on: multi-player no-limit Texas hold’em. But the game theory used in the current software falls down when there’s more than one opponent, and it’s not clear what technique to use instead.
Still, given the progress machine learning is currently making, and the fact that other AI poker bots are also being developed, that seemingly impossible challenge may not remain impossible for long.
