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Google Used Machine Learning To Master Game of Go

Google Used Machine Learning To Master Game of Go

Enterprise & IT Jan 27,2016 0

Google has developed the first artificial-intelligence (AI) software that learned to play an ancient Chinese board game called Go and is capable of beating professional human players. The game of Go originated in China more than 2,500 years ago. The rules of the game are simple: Players take turns to place black or white stones on a board, trying to capture the opponent's stones or surround empty space to make points of territory. But as simple as the rules are, Go is a game of profound complexity, as there are countless possible positions (!). This complexity is what makes Go hard for computers to play, and therefore an irresistible challenge to artificial intelligence (AI) researchers.

To date, Go has thwarted AI researchers; computers still only play Go as well as amateurs. Traditional AI methods don?t have a chance in Go.

Google DeepMind, the London research group behind the project, built a system, AlphaGo, that combines an advanced tree search with deep neural networks. These neural networks take a description of the Go board as an input and process it through 12 different network layers containing millions of neuron-like connections. One neural network, the "policy network," selects the next move to play. The other neural network, the "value network," predicts the winner of the game. Google's researhers trained the neural networks on 30 million moves from games played by human experts, until it could predict the human move 57 percent of the time. But our goal is to beat the best human players, not just mimic them. To do this, AlphaGo learned to discover new strategies for itself, by playing thousands of games between its neural networks, and adjusting the connections using a trial-and-error process known as reinforcement learning.

Google held a tournament between AlphaGo and the other top programs at the forefront of computer Go. AlphaGo won all but one of its 500 games against these programs. So the next step was to invite the reigning three-time European Go champion Fan Hui - an elite professional player who has devoted his life to Go since the age of 12 - to Google' London office for a challenge match. In a closed-doors match last October, AlphaGo won by 5 games to 0. It was the first time a computer program has ever beaten a professional Go player. You can find out more in this paper, which was published in Nature today.

In March, AlphaGo will face its ultimate challenge: a five-game challenge match in Seoul against the legendary Lee Sedol - the top Go player in the world over the past decade.

Tags: Machine learningGoogle
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