Consider this, you are face to face with your toughest competitor, playing Texas Hold’em Poker. You know you have a strong hand, but it can be beat. Your opponent raises, you think about your cards again. Not able to look your opponent in the eye, you fold. There are no tells when you are playing a computer.
A $50,000 face-off between a poker-playing computer and 2 of the world’s impressive poker professionals will take place on Monday in Vancouver, Canada. There is no way to determine or even guess who will bring home the prize.
The machine, nicknamed Polaris by its University of Alberta originators, is designed to play to its opponent’s weaknesses, effortlessly switching from guarded under-betting to assertive bluffing. “With poker, the key thing is unpredictability,” said Jonathan Schaeffer, one of the lead artificial intelligence researchers on the Polaris project. “A computer is very good at predicting odds … it can do that very quickly. But in poker, if you play cautiously, then the opponent can pick up on that and they start exploiting that … so the goal of (Polaris) is to be unpredictable for the human.”
The high-stakes tournament is part of the Association for the Advancement of Artificial Intelligence conference being held at a Vancouver hotel. An audience will be on hand to watch professional players Phil Laak and Ali Eslami in mind-vs. -machine match with the simulator, each with the opportunity to take home $25,000 if they win all four of their games. Both Laak and Eslami are world renowned for their poker prowess.
The Man-Machine competitions have grabbed a hold of the imagination before; one of the best examples of this was the 1997 match between IBM’s “Deep Blue” chess program and Garry Kasparov, world known grandmaster. Technology has improved since then, and now computers are ready to face a more difficult challenge – trying to wrest supremacy from the humans at poker. While artificial intelligence research has created computers that are virtually unbeatable in strategic games such as chess and checkers, Polaris may have a tougher time with the role of pure luck in poker.
“I’m not at all sure that the computer is going to win this thing, precisely because it is so difficult to learn about the style of your opponent,” said Oliver Schulte, a cognitive scientist who worked with the Polaris project creators.
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