ShareThis Page
Technology

CMU team publishes paper on how their poker-playing AI beat the best humans

Aaron Aupperlee
| Monday, Dec. 18, 2017, 10:57 a.m.
Professional poker player Jason Les speaks with Carnegie Mellon University’s School of Computer Science Professor Tuomas Sandholm while Libratus, an artificial intelligence(AI) program playing Heads-Up, No-Limit Texas Hold’em at Rivers Casino on Jan. 11, 2017. Libratus was developed at Carnegie Mellon University’s School of Computer Science.
Nate Smallwood | Tribune-Review
Professional poker player Jason Les speaks with Carnegie Mellon University’s School of Computer Science Professor Tuomas Sandholm while Libratus, an artificial intelligence(AI) program playing Heads-Up, No-Limit Texas Hold’em at Rivers Casino on Jan. 11, 2017. Libratus was developed at Carnegie Mellon University’s School of Computer Science.
Professional poker player Jason Les and Noam Brown, a PhD student at Carnegie Melon participate in a competition against Libratus, an artificial intelligence(AI) program playing Heads-Up, No-Limit Texas Hold’em at Rivers Casino on Jan. 30, 2017. Libratus was developed at Carnegie Mellon University’s School of Computer Science.
Nate Smallwood | Tribune-Review
Professional poker player Jason Les and Noam Brown, a PhD student at Carnegie Melon participate in a competition against Libratus, an artificial intelligence(AI) program playing Heads-Up, No-Limit Texas Hold’em at Rivers Casino on Jan. 30, 2017. Libratus was developed at Carnegie Mellon University’s School of Computer Science.
Professional poker player Daniel McAulay squares off against Libratus, an artificial intelligence(AI) program playing Heads-Up, No-Limit Texas Hold’em at Rivers Casino on Jan. 11, 2017. Libratus was developed at Carnegie Mellon University’s School of Computer Science.
Nate Smallwood | Tribune-Review
Professional poker player Daniel McAulay squares off against Libratus, an artificial intelligence(AI) program playing Heads-Up, No-Limit Texas Hold’em at Rivers Casino on Jan. 11, 2017. Libratus was developed at Carnegie Mellon University’s School of Computer Science.
Professional poker player Daniel McAulay says he and other humans understimated Libratus, an artificial intelligence program playing heads-up, no-limit Texas Hold’em on Monday, Jan. 30, 2017, at Rivers Casino.
Nate Smallwood | Tribune-Review
Professional poker player Daniel McAulay says he and other humans understimated Libratus, an artificial intelligence program playing heads-up, no-limit Texas Hold’em on Monday, Jan. 30, 2017, at Rivers Casino.

Poker players rarely reveal their secrets or strategy.

But that's just what Libratus, possibly the best poker-playing artificial intelligence, did.

Tuomas Sandholm, a Carnegie Mellon University professor of computer science, and Noam Brown, a Ph.D. student in computer science at CMU, published a paper in Science that detailed how Libratus managed to beat four of the best no-limit Texas Hold'em poker players in the world this year.

In January, Libratus squared off against Jason Les, Dong Kim, Daniel McCauley and Jimmy Chou, four of the top professional, no-limit Texas Hold'em poker players in the world, during the 20-day, 120,000-hand Brains vs. AI challenge at Rivers Casino on Pittsburgh's North Shore. Libratus crushed the humans.

The humans never led. They came close on the sixth day of the challenge, but then the computer opened up a huge lead and never looked back. At the end of 20 days, Libratus has nearly 1.8 million in chips. The top-performing human, Dong Kim, lost about 86,000 chips.

So how did Libratus do it ? First, the AI made the game easier to understand.

There are 10(161) potential outcomes in the game of poker — that's a one followed by 161 zeros, potential outcomes in a game of poker. Libratus grouped similar hands, like a King-high flush and a Queen-high flush, and similar bet sizes to cut down that number.

Libratus then created a detailed strategy for how it would play the early rounds of the game and a less-refined strategy for the final rounds. As the game nears the end, Libratus refined the second strategy based on how the game had gone.

A third strategy was at work as well. In real-time, Libratus created another model based on how its play stacked up against the play of the humans. If the humans did something unexpected to Libratus, the AI accounted for it and built it into the strategy.

Instead of trying to exploit weaknesses in the play of the human, Libratus focused on improving its play.

Libratus wasn't just fun and games. It was serious science. The AI isn't poker-specific, Sandholm and Brown wrote.

"The techniques that we developed are largely domain independent and can thus be applied to other strategic imperfect-information interactions, including non-recreational applications," Sandholm and Brown concluded. "Due to the ubiquity of hidden information in real-world strategic interactions, we believe the paradigm introduced in Libratus will be critical to the future growth and widespread application of AI."

Aaron Aupperlee is a Tribune-Review staff writer. Reach him at aaupperlee@tribweb.com, 412-336-8448 or via Twitter @tinynotebook.

TribLIVE commenting policy

You are solely responsible for your comments and by using TribLive.com you agree to our Terms of Service.

We moderate comments. Our goal is to provide substantive commentary for a general readership. By screening submissions, we provide a space where readers can share intelligent and informed commentary that enhances the quality of our news and information.

While most comments will be posted if they are on-topic and not abusive, moderating decisions are subjective. We will make them as carefully and consistently as we can. Because of the volume of reader comments, we cannot review individual moderation decisions with readers.

We value thoughtful comments representing a range of views that make their point quickly and politely. We make an effort to protect discussions from repeated comments either by the same reader or different readers

We follow the same standards for taste as the daily newspaper. A few things we won't tolerate: personal attacks, obscenity, vulgarity, profanity (including expletives and letters followed by dashes), commercial promotion, impersonations, incoherence, proselytizing and SHOUTING. Don't include URLs to Web sites.

We do not edit comments. They are either approved or deleted. We reserve the right to edit a comment that is quoted or excerpted in an article. In this case, we may fix spelling and punctuation.

We welcome strong opinions and criticism of our work, but we don't want comments to become bogged down with discussions of our policies and we will moderate accordingly.

We appreciate it when readers and people quoted in articles or blog posts point out errors of fact or emphasis and will investigate all assertions. But these suggestions should be sent via e-mail. To avoid distracting other readers, we won't publish comments that suggest a correction. Instead, corrections will be made in a blog post or in an article.

click me