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This article documents the progress of significant human–computer chess matches.. Chess computers were first able to beat strong chess players in the late 1980s. Their most famous success was the victory of Deep Blue over then World Chess Champion Garry Kasparov in 1997, but there was some controversy over whether the match conditions favored the computer.
Fan Hui vs AlphaGo – Game 5. AlphaGo defeated European champion Fan Hui, a 2 dan professional, 5–0 in October 2015, the first time an AI had beaten a human professional player at the game on a full-sized board without a handicap. [19] [20] Some commentators stressed the gulf between Fan and Lee, who is ranked 9 dan professional. [21]
On December 5, 2017, the DeepMind team released a preprint paper introducing AlphaZero, [1] which would soon play three games by defeating world-champion chess engines Stockfish, Elmo, and the three-day version of AlphaGo Zero. In each case it made use of custom tensor processing units (TPUs) that the Google programs were optimized to use. [2]
Indeed, a human hasn't defeated a machine in a chess tournament in 15 years. It's an impressive technical achievement, but that dominance has also made top-level chess less imaginative, as players ...
[1] [2] It has long been considered a difficult challenge in the field of artificial intelligence (AI) and is considerably more difficult to solve than chess. [3] Many in the field considered Go to require more elements that mimic human thought than chess. [4] Mathematician I. J. Good wrote in 1965: [5] Go on a computer?
Cheating expert and statistician Kenneth W. Regan discusses how chess engines have transformed the game. A top expert on chess cheating explains how AI has transformed human play Skip to main content
In the first game of the first match, which took place from 10 to 17 February 1996, Deep Blue became the first machine to win a chess game against a reigning world champion under regular time controls. However, Kasparov won three and drew two of the following five games, beating Deep Blue by 4–2 at the close of the match. [16]
[2] While patiently accumulating an advantage may be a beneficial tactic against alpha-beta AIs who play tactically, MCTS-based AIs like AlphaGo may themselves play in this patient strategic manner. [2] Thus deliberately tactical play, which is a bad approach against alpha-beta, becomes a viable anti-computer tatctic against MCTS.