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The New Card Shark
By PETER WAYNER

WHEN an accountant named Chris Moneymaker won $2.5 million in the World Series of Poker last May, the chatter in the poker world wasn't focused on his skillful bluffing, his tremendous luck or even the aptness of his surname. Everyone wanted to know how a man who had never before sat down at a tournament table could clean out so many skilled professionals. While the Las Vegas hype machine focused on the rags-to-riches tale of a man who parlayed a $40 entrance fee into a huge pot, many poker players recognized that the amateur's success signaled the arrival of a new age in the game. Mr. Moneymaker may never have been in the same room as other players in a tournament of Texas Hold'em poker, but he had played extensively online, where the game is faster but the money is just as real. He was as much a rookie as Ichiro Suzuki, who joined the Seattle Mariners after nine years in the Japanese major leagues. The online poker saloons that nurtured Mr. Moneymaker, 27, are just the beginning. Many players hone their craft with simulation software that allows them to test strategies by playing out thousands or even millions of hands. Some researchers are building software opponents that use sophisticated concepts from economics and artificial intelligence to seek out the best strategy, then use the knowledge to beat human players. The experience of playing thousands of games in roadhouses and casinos is being eclipsed by a cyborg-like intelligence produced by humans weaned on machine play. The changes in the nature of the game are both subtle and striking. The advantages of some well-understood strategies are being tuned, and others are being abandoned. Some online enthusiasts, for instance, are even suggesting that the value of any information gleaned from watching the opponent's body for telltale tics or gestures is overrated. These so-called tells are too easily manipulated. More information comes in the pattern of bets, raises and calls. The money, they say, talks. The biggest factor propelling change may be the speed of technology. Players do not wait while someone shuffles and deals. Chips do not need to be counted or watched. Computers handle the accounting, often finishing hands in as little as 30 seconds. Steve Badger, the editor of the Web site playwinningpoker.com and winner of the 1999 World Series in a game called Omaha Hi-Lo, says that online poker halls are appealing because of their convenience. "You could play them every day," he said. "You're able to play two games at the same time. Or you can sit and read or vacuum or do any infinite number of things while waiting for the next hand." The online halls also offer substantially better rates. Most casinos pay for the lights and the dealer by subtracting either a fixed amount or a percentage from the pot. This levy, known as the rake, is often about $3 to $5 a hand in physical casinos, but about $1 or less online. The rake depends on the stakes, which can be lower than those at physical casinos. Some online tables have minimum bets as low as 25 cents, an amount that makes learning the game cheaper. The speed of the game, however, ends up raising the amount at risk because 60 to 100 hands can be played in an hour. Higher minimum bets of $5, $10 or more are also common at tables with the better players. Gautam Rao, a well-known Canadian player, said he stopped going to casinos in 2000, not long after his daughter was born, "because of the smoke and distance.'' "I told my wife I had to find a way to play online," he said. Now, he is able to play every night between 10 p.m. and 3 a.m. while his daughter sleeps in the next room. "The rake is much less," he said. "The number of hands is much more. There are never any misdeals. There are never any issues related to tipping. The average cost of winning a pot is so much less. It's so much more efficient." The speed of play lets players work through the thousands of apprentice hands faster while paying attention to the game itself, rather than the surroundings. "I think I learned it differently," Mr. Moneymaker said in a telephone interview. "I learned to play so many hands. You watch the fluctuation of betting patterns. It's a lot more difficult to read people online." The combination of distance and simplicity is worrying some regulators, who note that the Internet card rooms are often based in places like the Caribbean, out of reach of United States laws. While there seems to be little enforcement, the games take place in legal limbo. Physical casinos and opponents of gambling suggest that existing laws ban playing poker online to protect the gambler. Online players argue that the Web sites know that their long-term existence relies on providing a fair game for everyone. Mr. Moneymaker, like other players, refuses to answer questions about the topic. When tournament play online isn't enough, many players are turning to software programs that simulate the game. These let players explore all of the permutations of the game to develop a better strategy. Another successful amateur, the novelist and poet James McManus, turned the story of his experiences at the 2000 World Series into a best-selling book, "Positively Fifth Street: Murderers, Cheetahs, and Binion's World Series of Poker" (Farrar, Straus & Giroux, 2003). While Mr. McManus did not win outright, he made his way to the final table and finished fifth. In the book he describes how he built up the skills to compete at the World Series level by playing endlessly against programs like Turbo Texas Hold'em from Wilson Software. The programs can be useful for studying the nuances of the game. A gambler can focus on particular combinations of cards, then try all possible outcomes. Anyone with questions about the wisdom of drawing to an inside straight, for instance, can find numerical proof of the path's expected value. (Five sequential cards, like 7, 8, 9, 10 and jack, make a straight. A player missing a card in the middle, say the 8, is said to be drawing to an inside straight. If the player has four consecutive cards, say 7, 8, 9 and 10, then two cards - the 6 or jack - can complete the hand. Drawing to an outside straight is roughly twice as likely to be successful as searching to fill an inside straight.) "They're not just games, they're study tools," Mr. Badger said. "You deal the same starting hand against a programmed group of opponents and discover the hand that I thought was pretty good actually lost me a lot of money." These programmed opponents are designed to mirror various human archetypes, with styles that vary from cautious to free-spending. Bob Wilson, the president of Wilson Software, said the program uses a highly tuned table of strategies that vary with dozens of factors, including the number of players still competing for the pot, the position around the table, the potential strengths of the hands, and the potential of other hands on the table. While Mr. Wilson is proud of his artificial players, his main goal was not to beat humans but to teach humans to beat other humans, he said. Bots, after all, don't have money to lose. "The objective was to put a system together to allow some people to do some testing," he said. Others are delving deeper into the mathematics of the game and aiming to build bots that can dominate. Darse Billings, a Ph.D. student at the University of Alberta, is working with his professors to build a bot capable of beating all human players. They currently operate a free poker room online where the bots routinely defeat most humans (games.cs.ualberta.ca/webgames /poker). The heart of their current method exploits game theory to build a good model to determine when it makes sense to bet or fold. This branch of mathematics gained wide recognition after a book about John Nash, a pioneer in the area, was made into the Oscar-winning movie "A Beautiful Mind." Building a complete model of a poker game is not feasible because there are billions of possible outcomes. Instead, the team tried to simplify the model by combining similar hands. They ended up with seven possible classes of hands and used this to create a plan of action for the bots. "The program is the first decent approximation of a really balanced strategy," Mr. Billings said. "It does a really good job of bluffing with an appropriate frequency, as well as check raising and slow playing." Playing against one of Mr. Billings's bots can be unnerving for some of the better human players, who often rely on unbridled aggression to win. The machines don't feel challenged as humans do; they simply crunch more numbers to decide the proper response. Mr. Rao, a friend of Mr. Billings, played several thousand hands against the bots and lost frequently at the beginning. "It understood the math perfectly," Mr. Rao said. "It knows the value of any holding at any point in time, allowing it to make proper calls." For example, many poker players consider 10's and jacks to be relatively low cards with little winning potential, but game theory suggests that they can still win hands in some situations with few players. The bot used knowledge like this to good effect. "It will win its share of pots," Mr. Rao said. "If you think you can over-aggress it, you will lose." After several thousand hands, Mr. Rao shifted away from aggressive play. Instead of raising early and forcing the bots to react to his bets, he hung back more often to learn from their actions. This gave him more control, and he won more frequently. Mr. Rao said that experience taught him a lesson. "Whenever you enter a new situation, don't assume you can execute a strategy that will win,'' he said. "Be quiet and listen instead of presuming or assuming." Peter Muller, a friend of Mr. Rao's who has played against the same bot, said the approximations in the game-theory model left a weakness and limited the bot's chances to do more than break even. Game-theory models usually assume that every player uses the best possible strategy, something that rarely if ever happens with humans. "An optimal game theoretic strategy might ensure that you don't lose, but it won't be effective at exploiting an opponent's weaknesses," Mr. Muller said. "The best players learn how to exploit predictability, but don't do it often enough so that the opponents catch on." Mr. Billings is working on giving the next generation of bot the ability to track the behavior of an opponent and adapt to his moves. He believes that the foundation of game theory gives the bot the ability to manage losses, a crucial skill for winning in the long run. All of this knowledge can have a downside, because analysis can kill a game as easily as it can a joke. Games like tic-tac-toe are well understood and therefore rarely satisfying. While poker is far from being understood at the same level, the deeper knowledge of a broader range of players is squeezing the margins for everyone. Mr. Wilson spoke almost wistfully about the days in the early 1990's when card rooms first opened in California and began offering Texas Hold'em. "The games were crazy and loose," he said. "The games were wild. There were very few people who understood the game. Then the real turkeys ran out of money and stopped playing. They got smarter and started understanding the more subtle areas of the game." When the skill is more even and well distributed, the effects of chance grow stronger, leading to more turbulence in the game. No one knows this better than Robert Varkonyi, the unknown who surprised everyone by winning the World Series of Poker in 2002. This year he was eliminated the first day.


 

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