Nevertheless, it was believed that while a game such as Go, might fit this form of software engineering, it would never really work for a chess program. As a sidenote, Feng Hsu and the Deep Blue team did eventually publish papers describing the entire thing inside and out. In a sense, this was the equivalent of IBM creating the world-beating Deep Blue, and then publishing blueprints the very same day so that anyone could build their own. It was the result of a powerful artificial intelligence technique known as deep reinforcement learning, which built a neural network combined with the Monte Carlo Tree Search that allowed the program, equipped with just the barebones rules of the game, to play itself millions upon millions of times, learning as it went until it reached, as was the case, superhuman playing strength.Īll the more remarkable was that the Deep Mind group published peer-reviewed papers that detailed exactly how it was achieved. When Alpha Go, and then Alpha Go Zero, was released, it cracked one of the most challenging strategic games in the world, and one that experts all over had thought would resist for at least another decade. Still no ChessBase Account? learn more > The ultimate chess experience every day, Pla圜 welcomes 20,000 chess players from all around the world – from beginner to grandmaster.Memorize it easily move by move by playing against the variation trainer.

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