Bluffing Poker Good poker players learn from the behavior of their foes and adapt on the fly

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PartyPoker marketing director Vikrant Bhargava said he wasn't pleased to learn that many of the poker bot World Series contestants honed their skills on his site, adding that eventually all such cheats get caught. Other sites don't care whether users are human, he said, because the house takes the same percentage of the pot no matter who's playing. But Bhargava said PartyPoker has 100 employees looking for robots, collusion among players and other scams.

Gaming companies won't disclose all their secrets for sniffing out bots, but some of the techniques are simple. Any person playing three tables simultaneously for 48 hours without a bathroom break, for example, or invariably taking exactly one second to bet, is not a person.

Computer gaming experts said the robots have some major hurdles to overcome before they have a chance against the world's top human beings -- especially in multi-player games with no betting limit, where the psychology is most important and the number of possible bets is much larger. Bluffing can be programmed: For every 100 basically worthless hands, for instance, a machine might be instructed to bet heavily five times.

A far bigger issue is the need for abstract pattern recognition. Computers are much worse than humans at anything vague, said poker pro Magriel, a 58-year-old former math professor and world backgammon champion.

At such tasks, "computers are basically idiots," Magriel said. "A computer has an enormous problem recognizing a face. A baby is better."

The need to recognize patterns comes when anyone new sits down at the table. Good poker players learn from the behavior of their foes and adapt on the fly. Computers can store and process millions of past hands, but they have too little data on each new competitor.

For that reason, Schaeffer's team has been focused for years on improving a program's ability to compete one-on-one and learn from as few as 50 hands. After that, the current version does well for a while, until a strong human opponent figures out its patterns. Then the person starts winning.

Magriel once predicted computers would never master backgammon. Now that he knows different, he thinks a better-than- human poker program is inevitable in two or three decades.

"It was a little depressing in chess and backgammon that computers got so good," he said. "In poker, it won't really depress me. I sort of expect it at some point."








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