Libratus Poker Paper
A research paper describing a key component of Libratus, an artificial intelligence that displayed its poker prowess earlier this year, won one of three best paper awards at the Neural Information Processing Systems (NIPS 2017) conference this week in Long Beach, Calif.
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. Libratus, an artificial intelligence developed by Carnegie Mellon University, made history by defeating four of the world’s best professional poker players in a marathon 20-day poker competition, called “Brains Vs. Artificial Intelligence: Upping the Ante” at Rivers Casino in Pittsburgh. In a paper published online yesterday by the journal Science, Tuomas Sandholm, CMU professor of computer science, and Noam Brown, a PhD student in the Computer Science Department, detail how their AI achieved superhuman performance at Heads-Up, No-Limit Texas Hold'em poker. 'Libratus' beat four of the world's best human players by breaking the.
Tuomas Sandholm, professor of computer science, and Noam Brown, a Ph.D. student in the Computer Science Department, will present their paper, 'Safe and Nested Subgame Solving for Imperfect-Information Games,' at the conference Tuesday afternoon.
Libratus bested four top professional players in Heads-Up, No-Limit Texas Hold'em during a 20-day marathon competition in January, Brains Vs. Artificial Intelligence: Upping the Ante. The AI led by a combined $1.8 million in chips after playing 120,000 hands. Libratus used the Pittsburgh Supercomputing Center's Bridges computer to compute its strategy before and during the Pittsburgh event.
The NIPS paper focuses on subgame solving, a process by which a game is decomposed into subgames that can be solved independently. Though it's not possible to solve subgames for an imperfect information game such as poker, it is possible to approximate solutions. Sandholm and Brown made subgame solving a key component of Libratus and developed new solving techniques that outperformed prior methods in theory and in practice.
Libratus Poker Paper Plate
In addition to the NIPS recognition, Libratus and the PSC also recently won the HPCwire Reader's Choice Award for Best Use of AI.
