An AI Bot Just Beat Poker Pros In Six-Player Texas Hold'em

14 July, 2019, 12:41 | Author: Sammy Rose
  • An AI Developed by Facebook and Carnegie Mellon Beats Champions of Poker

An AI poker gamer created by research scientists from Facebook AI and Carnegie Mellon University has defeated two of the World's best poker players.

Pluribus was developed by Tuomas Sandholm, Angel Jordan Professor of Computer Science, and Noam Brown, who is now finishing his doctorate in Carnegie Mellon's Computer Science Department as a research scientist at Facebook AI.

As a reminder, Pluribus' achievement comes after various other experiments on Libratus AI, which was able to defeat players in a two-player Poker setup. There were six players per game (sometimes five humans would play against Pluribus; sometimes five versions of the bot would play against one human). Traditionally, it's seen as a weak, non-sensical move that human players tend to avoid. Think of it like sitting down in a live poker room with four complete strangers and a computer.

'That's the same thing that humans try to do. Most people just can't'. Well, now Libratus's follow up - Pluribus - has taken away that crumb of comfort, something the researchers call a "recognised AI milestone".

So, Pluribus is a player that brings one's A game at all times because, frankly, there's nothing else for it to play. To translate, that is 48 big blinds per thousand hands, or 4.8 big blinds per hundred.

Pluribus was put against 12 players in two settings. The 13 pros who played against an individual Pluribus divided $50,000, depending on their performance. They included Chris Ferguson, Greg Merson, Darren Elias and Jimmy Chou. For any other type of usage, the parties have agreed that they can use the additional code as they wish.

For one, it's a multiplayer game, not mano a mano like the others. This is likely because even though they were not directly competing against each other, the scientists didn't want them adjusting their strategy based on the knowledge of the other person.

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The bot learned to pick its moments and then make huge bets and bluffs - bigger than most humans would make. Sean Ruane commented on Pluribus' "relentless consistency". Elias trailed Pluribus by 40 mbb/game and Ferguson was behind 25 mbb/game.

"Strategies are much harder to compute outside of two-player zero-sum games", explained Sandholm.

"It's safe to say we're at a superhuman level and that's not going to change."
There were options for Pluribus to veer from its bet restrictions if necessary.

"Pluribus achieved superhuman performance at multi-player poker, which is a recognized milestone in artificial intelligence and in game theory that has been open for decades". Training of Pluribus on a cloud service would cost just $150 while running it required a computer with two processors and 128 GB of memory, which was enough to play twice as fast as an average human player.

According to the creators of Pluribus, the technology could be used to solve a "wide variety of real-world problems" that, like in poker, involve actors who bluff, or hide key information.

Asked to describe the potential uses of the research in the future, Sandholm said strategic reasoning technologies have a range of applications from poker and video games, to strategy optimization in investment banking, political campaigns, and even steering evolution and biological adaptation "such as for medical treatment planning and synthetic biology and so on". "There were several plays that humans simply are not making at all, especially relating to its bet sizing".



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