VANCOUVER, British Columbia, July 25 — For anyone stuck on a casino stool, playing hours of video poker, rest assured: humans can still beat a computer.
But computers may soon dominate on the felt-top table, as they have on the chessboard.
In a match of wits between man and machine this week, a software program running on an ordinary laptop computer fought a close match, but lost to two well-known professional human poker players.
The contest, which was billed as the “First Man-Machine Poker Championship” and which offered prize money totaling $50,000, pitted two professionals, Phil Laak and Ali Eslami, against a program written by a team of artificial intelligence researchers from the University of Alberta. They gave it a name that probably no gambler would ever choose as a nickname, Polaris.
Poker is thought to be a more difficult challenge for software designers than games like chess and checkers. Computer scientists have to develop different strategies and algorithms to deal with the uncertainties introduced by the hidden cards held by each player as well as difficult-to-quantify risk-taking behaviors such as bluffing.
In the past, research has focused on chess and checkers. In 1997 Deep Blue, a supercomputer-based chess playing software system developed by I.B.M. researchers, beat Gary Kasparov, the world chess champion. The University of Alberta researchers won the world checkers championship in 1994, and earlier this month they reported that they had developed a program that cannot lose, and at best can be tied at checkers.
However, Jonathan Schaeffer, chairman of the University of Alberta computer science department and the researcher who initiated the poker playing research effort 16 years ago, said that the advances that are being made in the development of poker-playing software are likely to be more applicable in the real world than chess research.
“I contend that poker is harder than chess for computers, and the research results that come out of the work on poker will be much more generally applicable than what came out of the chess research,” he said.
Research interest has shifted to games like poker in recent years, in part because chess is no longer of keen interest and in part because rapid progress is being made in developing new algorithms with broad practical applications in areas such as negotiation and commerce, said Tuomas Sandholm, a Carnegie Mellon University computer scientist.
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But computers may soon dominate on the felt-top table, as they have on the chessboard.
In a match of wits between man and machine this week, a software program running on an ordinary laptop computer fought a close match, but lost to two well-known professional human poker players.
The contest, which was billed as the “First Man-Machine Poker Championship” and which offered prize money totaling $50,000, pitted two professionals, Phil Laak and Ali Eslami, against a program written by a team of artificial intelligence researchers from the University of Alberta. They gave it a name that probably no gambler would ever choose as a nickname, Polaris.
Poker is thought to be a more difficult challenge for software designers than games like chess and checkers. Computer scientists have to develop different strategies and algorithms to deal with the uncertainties introduced by the hidden cards held by each player as well as difficult-to-quantify risk-taking behaviors such as bluffing.
In the past, research has focused on chess and checkers. In 1997 Deep Blue, a supercomputer-based chess playing software system developed by I.B.M. researchers, beat Gary Kasparov, the world chess champion. The University of Alberta researchers won the world checkers championship in 1994, and earlier this month they reported that they had developed a program that cannot lose, and at best can be tied at checkers.
However, Jonathan Schaeffer, chairman of the University of Alberta computer science department and the researcher who initiated the poker playing research effort 16 years ago, said that the advances that are being made in the development of poker-playing software are likely to be more applicable in the real world than chess research.
“I contend that poker is harder than chess for computers, and the research results that come out of the work on poker will be much more generally applicable than what came out of the chess research,” he said.
Research interest has shifted to games like poker in recent years, in part because chess is no longer of keen interest and in part because rapid progress is being made in developing new algorithms with broad practical applications in areas such as negotiation and commerce, said Tuomas Sandholm, a Carnegie Mellon University computer scientist.
Discuss Add this link to... Bury
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