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In major AI win, Libratus beats four top poker pros

Thor Olavsrud | Feb. 2, 2017
Libratus, artificial intelligence developed by Carnegie Mellon University, has beaten four of the best heads-up no-limit Texas hold'em poker players in the world in a 20-day competition. Its mastery of imperfect information suggests a multitude of real-world applications.

"The best AI's ability to do strategic reasoning with imperfect information has now surpassed that of the best humans," Sandholm said.

AI has head its head in the game

Artificial intelligences have challenged humans in all manner of games over the past several decades. In 1997, IBM chess computer Deep Blue defeated world chess champion Garry Kasparov. In 2011, IBM Watson defeated Ken Jennings and Brad Ruttner, the two winningest Jeopardy players in that game show's history. In 2015, Google DeepMind's AlphaGo defeated South Korean professional Go player Lee Sedol, considered one of the best players in the world.

But heads-up no-limit Texas hold'em has widely been considered the far frontier. Unlike the other games, it is a game of imperfect information — the players know only some of the cards in play, and they can bluff and use other ploys to mislead their opponents. It's complexity is immense. The game features 10160 (the number 1 followed by 160 zeroes) information sets. Each set is characterized by the path of play in the hand as perceived by the player whose turn it is. The game's 10160 information sets represent significantly more information sets than the number of atoms in the universe.

To play, the AI must make decisions without knowing all the cards in play, while trying to sniff out bluffing by its opponent.

Why Libratus' win matters

Libratus' victory is a new milestone in AI that has implication for any realm in which information is incomplete and opponents sow misinformation, Frank Pfenning, head of the Computer Science Department in CMU's School of Computer Science, said in a statement Tuesday. Those areas range from business negotiation to military strategy, cybersecurity and medical treatment.

"The computer can't win at poker if it can't bluff," Pfenning said. "Developing an AI that can do that successfully is a tremendous step forward scientifically and has numerous applications. Imagine that your smartphone will someday be able to negotiate the best price on a new car for you. That's just the beginning."

Libratus, though, had significantly more computing power behind it than your phone. It used the Pittsburgh Supercomputing Center's Bridges computer to compute its strategy before and during the event. Throughout the competition, Libratus used about 600 of Bridges' 846 compute nodes. Bridges' total speed is 1.35 petaflops, about 7,250 times as fast as a high-end laptop, and its memory is 274 terabytes, about 17,500 as much as that laptop would have.

Throughout the tournament, Libratus leveraged about 19 million core hours of computing and a knowledge base of 2,600 TB of information, said Nick Nystrom, senior director of research and principal investigator for the National Science Foundation-funded Bridges system at the Pittsburgh Supercomputing Center (PSC). In all, Libratus used about 46 percent of Bridges' computational capacity.

 

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