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Previous groundbreaking poker bots focused on a few different kinds of two-player poker. The bot quickly became a stronger player. Ultimately, Elias says Pluribus could spell the end of high-stakes online poker. That's what Elias found when he played against it. Regardless of how many players are involved, poker is simply a really tough game to program for because there's so much information that isn't out in the open, like it is in chess, for example. NPR Shop. But even though there's no fail-safe strategy to win, Brown says, Pluribus still outperforms the best humans. In artificial intelligence, it's a milestone when a computer program can beat top players at a game like chess. Facebook AI Research hide caption. Their research was published today in the journal Science. Brown says their AI technology could eventually be useful in other situations where there are multiple people involved and a lot of unknown variables, like getting a self-driving car through traffic. But a game like poker, specifically six-player Texas Hold 'em, has been too tough for a machine to master β€” until now. Pluribus β€” so-named because it takes on many opponents at once β€” learns by playing against itself over and over and remembering which strategies worked best. Brown, Pluribus' developer, says it's exciting that a bot could teach humans new strategies and ultimately improve the game. Pluribus eventually stopped limping as it became a stronger player. A bot named Pluribus crushed some of the world's best poker players using brash and unorthodox strategies. It won. During one experiment, the poker bot Pluribus played against five professional players. Limping means making the smallest bet possible to stay in the hand, instead of raising or folding. The bots will always be better than us. July 11, PM ET. Pluribus also confirmed something that many poker pros already suspected β€” "limping" is almost never a good strategy. A superhuman poker bot is also humbling and a little sad, Elias says. The cards are hidden. Ultimately, the machine came out ahead of Elias. Enlarge this image. The bot was excellent at varying its strategy even when dealt the exact same hand, Elias says, "which is pretty tough to play against because you can't really pick up a pattern. And the bot's success has implications beyond poker. Which was pretty scary," Elias said. Because only two players are involved, the bots could figure out a perfect strategy for each game β€” one that would eventually win every time. Four-time World Poker Tour title holder Darren Elias helped test the program's skills, playing Texas Hold 'em against a whole table of the bots. So scientists tried a different experiment in which they put one bot up against a full table of pro players. Accessibility links Skip to main content Keyboard shortcuts for audio player. And it won again. That didn't work in six-player poker games like no-limit Texas Hold 'em, Brown says. The easiest way to quantify how well Pluribus did was by how much money it was winning.

Merrit Kennedy. As Pluribus taught itself to play, some of the tactics it came up with were surprising. Facebook AI Research.

He'd take on four tables full of them at a time, and he'd alert the computer scientists who designed the bot when it made a mistake. Heard on All Things Considered. There are a couple of reasons why multi-player poker has been a challenge for AI programs. Facebook Twitter Flipboard Email. Those games have a lot more variables. Researchers say they have designed a bot called Pluribus capable of taking on poker professionals in the most popular form of poker and winning. The bot learned to pick its moments and then make huge bets and bluffs β€” bigger than most humans would make.