09-07-2019, 12:37 PM
Poker has long been a formidable challenge facing the field of AI. Players doesn’t know their opponents’ cards or thought process in bluffing or strategy, unlike other games such as chess or Go, which do not have this hidden element. This makes existing successful machine learning strategies ineffective in poker. In July, however, a program named Pluribus, created by Carnegie Mellon researchers in collaboration with Facebook’s AI division, defeated professionals in six-player no-limit Texas Hold’em poker, the most popular style of the game in the world. This accomplishment marks the first time a computer has beaten top humans in a poker game with more than two players or teams.
“Pluribus is a very hard opponent to play against. It’s really hard to pin him down on any kind of hand,” Chris Ferguson, a six-time World Series of Poker champion and one of the 12 pros drafted against the AI, said in a press statement. In a paper published in Science, the scientists behind Pluribus say the victory is a significant milestone in AI research. Although machine learning has already reached superhuman levels in board games like chess and Go, and computer games like Starcraft II and Dota, six-person no-limit Texas Hold ‘em represents, by some measures, a higher benchmark of difficulty. If you are in lack of Facebook Poker Chips, visit our site 777chips.com, a reliable and cheap online in-game currency store.
Pluribus' dominance over the mere mortals represents a breakthrough that might lead to applications of AI in real-world situations. That's because we often deal with multiple people and unknown information when it comes to things like political campaigns, online auctions and cybersecurity threats. AI could help businesses come up with the best strategies to handle those situations, research scientists say.
Though real-world applications for Pluribus may be a ways out, there are some poker-related tips that humans can take from it today, Brown said. For instance, it would, in some situations, bet much higher amounts of money than humans tend to — a move that pros indicated could be smart in some cases. And it went against conventional poker wisdom by determining that a strategy known as "donk betting," where a player begins a round by betting after ending the previous round with a call, could be a good play.
“Pluribus is a very hard opponent to play against. It’s really hard to pin him down on any kind of hand,” Chris Ferguson, a six-time World Series of Poker champion and one of the 12 pros drafted against the AI, said in a press statement. In a paper published in Science, the scientists behind Pluribus say the victory is a significant milestone in AI research. Although machine learning has already reached superhuman levels in board games like chess and Go, and computer games like Starcraft II and Dota, six-person no-limit Texas Hold ‘em represents, by some measures, a higher benchmark of difficulty. If you are in lack of Facebook Poker Chips, visit our site 777chips.com, a reliable and cheap online in-game currency store.
Pluribus' dominance over the mere mortals represents a breakthrough that might lead to applications of AI in real-world situations. That's because we often deal with multiple people and unknown information when it comes to things like political campaigns, online auctions and cybersecurity threats. AI could help businesses come up with the best strategies to handle those situations, research scientists say.
Though real-world applications for Pluribus may be a ways out, there are some poker-related tips that humans can take from it today, Brown said. For instance, it would, in some situations, bet much higher amounts of money than humans tend to — a move that pros indicated could be smart in some cases. And it went against conventional poker wisdom by determining that a strategy known as "donk betting," where a player begins a round by betting after ending the previous round with a call, could be a good play.