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Can AI beat the best at Texas hold'em?

Thor Olavsrud | Jan. 23, 2017
Heads-up no-limit Texas hold'em may be the final frontier in the battle of man vs. machine. Artificial intelligence developed by a Carnegie Mellon University professor and a Ph.D student is taking on four of the top pros in the world to show that AI can master games of imperfect information.

Nearly two years ago, Claudico, an AI developed by Sandholm and his Ph.D student Noam Brown, took on four of the top heads-up, no-limit Texas hold'em players in the world: Dong Kim, Jason Les, Bjorn Li and Doug Polk. From April 24 to May 8, 2015, Claudico played 20,000 hands against each player (80,000 hands total) for a $100,000 prize (donated by Microsoft Research and Rivers Casino). When the dust cleared, Polk, Kim and Li has more chips than Claudico, while Les trailed.

While the humans won in absolute terms, Sandholm says the result was a statistical tie - the participants didn't play enough hands to make a significant statistical determination.

A win (at least a tie) for humans

"The humans won; as a group, they won," he says. "But we couldn't get a statistically significant result on that. Even playing against those absolute, top players, it was a statistical tie. Certainly the AI was not better."

Determined to do better, Sandholm and Brown started over from scratch. In 2016, they developed a new poker-playing AI named Tartanian. They entered a "dumbed down" version of Tartanian, Baby Tartanian 8, in the 2016 Annual Computer Poker Competition and won both the Total Bankroll and Bankroll Instant Run-off categories. Sandholm explains Baby Tartanian 8 was "dumbed down" in that it had to be limited to the amount of memory allowed by the competition.

Then, in February 2016, Sandholm and Brown started over again, with an eye toward a second match-up between their AI and top heads-up, no-limit pros. They created Libratus. As with the other AI, they didn't write a strategy for Libratus. Instead, they wrote the algorithm that Libratus uses to compute its strategy.

For instance, he says, Libratus includes a new and faster equilibrium-finding method that identifies non-promising paths and starts to ignore them over time. It also has access to the Pittsburgh Supercomputing Center's Bridges supercomputer to perform live endgame-solving computations.

The new contest, "Brains vs. Artificial Intelligence: Upping the Ante," is currently ongoing at Rivers Casino in Pittsburgh. Pros Jason Les, Dong Kim, Daniel McAulay and Jimmy Chou are competing for a $200,000 prize this time around. The contest, which started on Jan. 11, will span 20 days, and the pros will play a collective total of 120,000 hands against Libratus.

As in the previous match, the contest will use duplicate matches to minimize the role of luck.

Reducing the variable

"We try to reduce the variance in this game by not allowing the computer to be lucky or the human to be lucky," Sandholm says. "We pair the players up."

For instance, if Jason Les and Dong Kim are paired, and Les gets a certain set of cards against the computer in a particular hand, the computer will get that same set of cards in a hand against Kim, and vice versa.

 

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