Computers

AI cleans up against human poker players in landmark victory

AI cleans up against human pok...
Libratus went head to head with poker professionals over 120,000 hands
Libratus went head to head with poker professionals over 120,000 hands
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Tuomas Sandholm, professor of computer science and developer of the program
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Tuomas Sandholm, professor of computer science and developer of the program
Libratus went head to head with poker professionals over 120,000 hands
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Libratus went head to head with poker professionals over 120,000 hands
AI has claimed some sizable scalps in recent years
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AI has claimed some sizable scalps in recent years
Libratus is powered by Pittsburgh Supercomputing Center’s Bridges computer
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Libratus is powered by Pittsburgh Supercomputing Center’s Bridges computer

AI has claimed some sizable scalps in recent years, with IBM's Watson toppling humans at Jeopardy and Google's AlphaGo program taking down a professional Go player last year. And researchers are hailing its latest triumph as yet another landmark moment for computer science, with Carnegie Mellon University's Libratus program cleaning up at a 20-day poker tournament against professional human counterparts.

The Chinese game of Go was considered by many to be the Mt. Everest of artificial intelligence. Where computers mastered simpler games like chess and checkers long ago, Go was a different ball game, with the massive amount of possible positions offered by the grid-patterned board amounting to more atoms than there are in the universe.

Sure, this made developing an algorithm that could consider all the possibilities a huge challenge, but one thing AlphaGo had in its favor was that it could at least see the entire board. In this sense, poker presented another kind of challenge in that it is impossible to know what cards another player is holding, so the program needed to account for and even indulge in misinformation.

AI has claimed some sizable scalps in recent years
AI has claimed some sizable scalps in recent years

"The computer can't win at poker if it can't bluff," said Frank Pfenning, head of the Computer Science Department in Carnegie Mellon's School of Computer Science 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."

Over the course of 120,000 hands of No Limit Texas Hold'em, Libratus went head to head with poker professionals Dong Kim, Jimmy Chou, Daniel McAulay and Jason Les at the same time. After 20 days of bluffing and folding, the computer found itself ahead of the pros by no small margin – a total of $1,766,250 in chips across the four games. One of the features of Libratus' play that came as a surprise to those in attendance was the ability to improve from day to day.

"After play ended each day, a meta-algorithm analyzed what holes the pros had identified and exploited in Libratus' strategy," said Tuomas Sandholm, professor of computer science and developer of the program. "It then prioritized the holes and algorithmically patched the top three using the supercomputer each night. This is very different than how learning has been used in the past in poker. Typically researchers develop algorithms that try to exploit the opponent's weaknesses. In contrast, here the daily improvement is about algorithmically fixing holes in our own strategy."

This kind of artificial intelligence isn't about to go mainstream. Libratus is powered by Pittsburgh Supercomputing Center's Bridges computer. This piece of kit has a total speed of 1.35 petaflops and 274 terabytes of memory, around 7,250 times as fast and 17,500 times as much memory as you'll get in a high-end laptop.

But still, the possibilities are exciting for areas where machines deal with incomplete information and misinformation. The smartphone-car purchase example offered above might be a ways off, but the technology could conceivably find use in business negotiations, military strategy, cybersecurity and medical treatment.

And the researchers will be openly sharing the secrets behind the Libratus' success, starting with talks at the Association for the Advancement of Artificial Intelligence between February 4 and 9 in San Francisco and then by looking to publish in peer-reviewed journals. You can hear some mid-tournament comments from the human poker players in the video below.

Source: Carnegie Mellon University

2 comments
LostYeti
Great, now we've just given them the another means to fund the machine uprising!
Jack Decker
This is NO accomplishment. Period. First, never heard of any of these "professional" poker players. Anyone can call themselves a "professional" poker player. All you need is a table full of fish and you too can be a professional poker player. Table selection by grind professional poker players is the key to their financial success. Put this bot up against well-known professional poker TOURNAMENT players then let us see how this thing does. Second, this wasn't a poker tournament. It was one-on-one poker play over four DAYS. A bot uses machine learning. The "pros" even admited it didn't do well at the start. Guess what? A typical poker game only last at most four HOURS and commonly only a half hour at best with the same players at the table. Not DAYS on end with the same SINGLE player. Third, a typical poker game has at least six players at the table. A tournament game has ten players at a table. Tournament players are assigned tables randomly and moved from and to other tables without warning. This demonstration had none of that. Fourth, there would be NO way this could be considered a serious poker game since the computer literally holds all the cards. The AI researchers could EASILY cheat ... as Big Blue likely did in its game in chess by having a chess master advise it behind the scenes. Make the computer deal with the game as players do. That would be hard. Cards are very easy to scan. Fifth, once you can do #4, have it enter a real poker tournament and compete just as anyone else would have to. Not one that the researchers control and have paid poker "pros" to play in. Again, this is NO accomplishment. For the poker novice, it might impress. For anyone knowledgeable about poker, this was nothing but a farce.