According to the Web site PokerScout.com, which bills itself as an Internet poker clearinghouse, there are more than 600 Web sites where people can play online. Mr. Jetter says that while Shanky does not have any “official relationships with the poker rooms,” some of them look the other way when bots play.

The science of poker bots is still in its infancy, which may be one reason that some gambling sites do not crack down on them. Unlike Watson, the I.B.M. computer that won on “Jeopardy!,” poker bots are not stellar players. But they are getting better, thanks to advances in the way computer scientists program software to play games.

“The large majority of bots are very bad,” said Darse Billings, a consultant to PokerStars and Full Tilt and the former chief of data analytics at Full Tilt. “More than 90 percent are losing money.”

It turns out to be a lot easier to build a perfect chess player than a poker whiz. Chess is a perfect information game: if you look at a chessboard, you know the exact state of the game from both players’ perspectives. And the rules of the game are not affected by chance, like the drawing of a card.

But in poker, an imperfect information game, there are many unknown variables. A player does not know his opponents’ cards and may not know their style of play — how aggressive they tend to be, for instance, or how often they bluff.

Unlike a chess bot, a poker bot does most of its work before the match, running millions of simulations before the first card is dealt. But even with the large amounts of memory available with today’s computers, storing — or even computing — information for every possible scenario would be implausible.

The best poker bots in the world include those from the University of Alberta Computer Poker Research Group, which is nearly 20 years old. Professor Michael Bowling, who has led the group since 2005, says the breakthrough came in 2003, when researchers decided to change their approach, shifting away from the methodology used to build chess bots.