VNUnet reports that US boffins at Carnegie Mellon University claim
to have created a smart learning program that can play a winning hand
of Texas hold 'em.
Professor Tuomas Sandholm and graduate student Andrew Gilpin are behind the game theory program that will compete in the Computer Poker Competition on 16-20 July in Boston run by the American Association for Artificial Intelligence.
The poker robot, called GS1, is not yet able to beat the best human players. However, it has outperformed the two leading 'pokerbots' in playing heads-up, limit Texas hold 'em in tests at Carnegie Mellon earlier this year. Both of GS1's opponents were commercially available programs that, like other pokerbots, incorporate the expertise of human poker players.
GS1, by contrast, develops its own strategy after performing an automated game theory-based analysis of poker rules.
Sandholm and Gilpin have since developed an improved version of their program, called GS2, which will compete in the competition.
Much as computer chess was an early test of artificial intelligence, computer poker has emerged as an even greater challenge.
"Poker is a very complex game," said Professor Sandholm. "Computer poker programs require really sophisticated technology."
Unlike chess, where the status of all of the chess pieces is known to both players, poker forces players to make decisions based on incomplete information. "You don't know what the other guy is holding," Professor Sandholm explained.
He added that the sheer number of possible combinations of cards dealt, cards on the table and bets in two-player Texas hold 'em makes it impossible for even the fastest computers fully to analyze every hand.
This element of uncertainty, and the vagaries of luck inherent in randomly dealt cards, make poker a better test of artificial intelligence than chess, according to Professor Sandholm.