Checkers, perhaps? Maybe it was something in the water, because University of Alberta's Schaeffer and many others also developed a checkers playing program that the university ultimately retired because it was unbeatable. According to the university's Web site, the Chinook project began in 1989 with the goal of developing a program capable of defeating the human World Checkers Champion. In 1990, Chinook became the first program in any game to win the right to play for a human world championship. The program lost the championship match in 1992, but became champion in 1994. By 1996, it became clear that the program was much stronger than any human, and Chinook was retired. Chinook won the World Man-Machine Championship (three years before the Deep Blue chess match) and in 1996 the Guinness Book of World Records recognized Chinook as the first program to win a human world championship, the university stated.
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Your move: According to the Backgammon.net Web site, a programmer by the name of Hans Berliner developed a backgammon program known as BKG that beat then world champion Luigi Villa. It won the match, 7-1, becoming the first computer program to defeat a world champion in any game, although this was mostly a matter of luck, as the computer happened to get better dice rolls than its opponent did in that match. According to the Web site, in the 1980s creators of backgammon-playing software began to have even more success with a neural network approach. TD-Gammon, developed by Gerald Tesauro of IBM, was the first of these computer programs to play at or close to the expert level. This program's neural network was trained using Temporal Difference learning applied to data generated from self-play. "This line of research has resulted in two modern commercial programs, Jellyfish and Snowie, the shareware BGBlitz, and the free software GNU Backgammon, that play on a par with the best human backgammon players in the world. It is worth noting that without their associated 'weights' tables, which represent hours or even months of tedious neural net training, these programs play no better than a human child would."