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Libratus is an artificial intelligence computer program designed to play poker, specifically heads up no-limitTexas hold 'em. Libratus' creators intend for it to be generalisable to other, non-Poker-specific applications. It was developed at Carnegie Mellon University, Pittsburgh.

  • Libratus is not the death of online poker, but online poker will definitely see the introduction of bots over the next decade. Online poker sites can delay the inevitable for a few years by practicing good computer detection, and being proactive, but I dont expect them to do much if it doesnt hurt their bottom line.
  • (source: wrote my thesis on poker AI a few months ago) There's no natural way of ranking players or rating their play for poker the way there is in games like chess. The group that played against Libratus are well-respected pros; two of them featured in an earlier match against Libratus' predecessor. The team that played against DeepStack is.
  • The first day of the Brains vs. AI poker tournament is in the books, and the Libratus bot from Carnegie Mellon University emerged as the clear winner, collecting $81,716 to the humans $7,228.

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Libratus the best poker bot, an AI Computer Recently Busted out Online Poker Pro Human Players Heads up and Winning in Poker Tournament Action One on One Libratus Computer Best Poker Bot Wins Poker Tournament Beating Pro Online Players showing the need to own the Best Poker Hud Software Available.

Background[edit]

While Libratus was written from scratch, it is the nominal successor of Claudico. Like its predecessor, its name is a Latin expression and means 'balanced'.

Libratus was built with more than 15 million core hours of computation as compared to 2-3 million for Claudico. The computations were carried out on the new 'Bridges' supercomputer at the Pittsburgh Supercomputing Center. According to one of Libratus' creators, Professor Tuomas Sandholm, Libratus does not have a fixed built-in strategy, but an algorithm that computes the strategy. The technique involved is a new variant of counterfactual regret minimization,[1] namely the CFR+ method introduced in 2014 by Oskari Tammelin.[2] On top of CFR+, Libratus used a new technique that Sandholm and his PhD student, Noam Brown, developed for the problem of endgame solving. Their new method gets rid of the prior de facto standard in Poker programming, called 'action mapping'.

As Libratus plays only against one other human or computer player, the special 'heads up' rules for two-player Texas hold 'em are enforced.

2017 humans versus AI match[edit]

From January 11 to 31, 2017, Libratus was pitted in a tournament against four top-class human poker players,[3] namely Jason Les, Dong Kim, Daniel McAulay and Jimmy Chou. In order to gain results of more statistical significance, 120,000 hands were to be played, a 50% increase compared to the previous tournament that Claudico played in 2015. To manage the extra volume, the duration of the tournament was increased from 13 to 20 days.

The four players were grouped into two subteams of two players each. One of the subteams was playing in the open, while the other subteam was located in a separate room nicknamed 'The Dungeon' where no mobile phones or other external communications were allowed. The Dungeon subteam got the same sequence of cards as was being dealt in the open, except that the sides were switched: The Dungeon humans got the cards that the AI got in the open and vice versa. This setup was intended to nullify the effect of card luck.

The prize money of $200,000 was shared exclusively between the human players. Each player received a minimum of $20,000, with the rest distributed in relation to their success playing against the AI. As written in the tournament rules in advance, the AI itself did not receive prize money even though it won the tournament against the human team.

During the tournament, Libratus was competing against the players during the days. Overnight it was perfecting its strategy on its own by analysing the prior gameplay and results of the day, particularly its losses. Therefore, it was able to continuously straighten out the imperfections that the human team had discovered in their extensive analysis, resulting in a permanent arms race between the humans and Libratus. It used another 4 million core hours on the Bridges supercomputer for the competition's purposes.

Strength of the AI[edit]

Libratus had been leading against the human players from day one of the tournament. The player Dong Kim was quoted on the AI's strength as follows: 'I didn’t realize how good it was until today. I felt like I was playing against someone who was cheating, like it could see my cards. I’m not accusing it of cheating. It was just that good.'[4]

At the 16th day of the competition, Libratus broke through the $1,000,000 barrier for the first time. At the end of that day, it was ahead $1,194,402 in chips against the human team. At the end of the competition, Libratus was ahead $1,766,250 in chips and thus won resoundingly. As the big blind in the matches was set to $100, Libratus winrate is equivalent to 14.7 big blinds per 100 hands. This is considered an exceptionally high winrate in poker and is highly statistically significant.[5]

Of the human players, Dong Kim came first, MacAulay second, Jimmy Chou third, and Jason Les fourth.

NameRankResults (in chips)
Dong Kim1-$85,649
Daniel MacAulay2-$277,657
Jimmy Chou3-$522,857
Jason Les4-$880,087
Total:-$1,766,250

Libratus Poker Reddit Game

Other possible applications[edit]

While Libratus' first application was to play poker, its designers have a much broader mission in mind for the AI.[6] The investigators designed the AI to be able to learn any game or situation in which incomplete information is available and 'opponents' may be hiding information or even engaging in deception. Because of this Sandholm and his colleagues are proposing to apply the system to other, real-world problems as well, including cybersecurity, business negotiations, or medical planning.[7]

See also[edit]

Libratus Poker Reddit Streams

References[edit]

  1. ^Hsu, Jeremy (10 January 2017). 'Meet the New AI Challenging Human Poker Pros'. IEEE Spectrum. Retrieved 2017-01-15.
  2. ^Brown, Noam; Sandholm, Tuomas (2017). 'Safe and Nested Endgame Solving for Imperfect-Information Games'(PDF). Proceedings of the AAAI workshop on Computer Poker and Imperfect Information Games.
  3. ^Spice, Byron; Allen, Garrett (January 4, 2017). 'Upping the Ante: Top Poker Pros Face Off vs. Artificial Intelligence'. Carnegie Mellon University. Retrieved 2017-01-12.
  4. ^Metz, Cade (24 January 2017). 'Artificial Intelligence Is About to Conquer Poker—But Not Without Human Help'. Wired. Retrieved 2017-01-24.
  5. ^'Libratus Poker AI Beats Humans for $1.76m; Is End Near?'. PokerListings. 30 January 2017. Retrieved 2018-03-16.
  6. ^Knight, Will (January 23, 2017). 'Why it's a big deal that AI knows how to bluff in poker'. MIT Technology Review.
  7. ^'Artificial Intelligence Wins $800,000 Against 4 Poker Masters'. Interesting Engineering. 27 January 2017.

External links[edit]

  • Brains versus Artificial Intelligence official website at the Rivers Casino
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