Watch AlphaGo take on Lee Sedol, the world’s top Go player

Watch AlphaGo take on Lee Sedol, the world’s top Go player, in the final match of the Google DeepMind challenge.

Match score: AlphaGo 3 – Lee Sedol 1.
[Game five: Seoul, South Korea, 15th March at 13:00 KST; 04:00 GMT; for US at -1 day (14th March) 21:00 PT, 00:00 ET.]

The Game of Go 

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. As simple as the rules are, Go is a game of profound complexity. There are more possible positions in Go than there are atoms in the universe. That makes Go a googol times more complex than chess. Go is played primarily through intuition and feel, and because of its beauty, subtlety and intellectual depth it has captured the human imagination for centuries. AlphaGo is the first computer program to ever beat a professional, human player. Read more about the game of Go and how AlphaGo is using machine learning to master this ancient game.

Match Details 

In October 2015, the program AlphaGo won 5-0 in a formal match against the reigning 3-times European Champion, Fan Hui, to become the first program to ever beat a professional Go player in an even game. Now AlphaGo will face its ultimate challenge: a 5-game challenge match in Seoul against the legendary Lee Sedol, the top Go player in the world over the past decade, for a $1M prize. For full details, see the press release.

The matches were held at the Four Seasons Hotel, Seoul, South Korea, starting at 13:00 local time (04:00 GMT; day before 20:00 PT, 23:00 ET) on March 9th, 10th, 12th, 13th and 15th.

The matches were livestreamed on DeepMind’s YouTube channel as well as broadcast on TV throughout Asia through Korea’s Baduk TV, as well as in China, Japan, and elsewhere.Match commentators included Michael Redmond, the only professional Western Go player to achieve 9 dan status. Redmond commentated in English, and Yoo Changhyuk professional 9 dan, Kim Sungryong professional 9 dan, Song Taegon professional 9 dan, and Lee Hyunwook professional 8 dan commentated in Korean alternately.The matches were played under Chinese rules with a komi of 7.5 (the compensation points the player who goes second receives at the end of the match). Each player received two hours per match with three lots of 60-second byoyomi (countdown periods after they have finished their allotted time).

How AlphaGo Mastered the Game of Go with Deep Neural Networks

The game of Go has long been viewed as the most challenging of classic games for artificial intelligence due to its enormous search space and the difficulty of evaluating board positions and moves.

Google DeepMind introduced a new approach to computer Go with their program, AlphaGo, that uses value networks to evaluate board positions and policy networks to select moves. These deep neural networks are trained by a novel combination of supervised learning from human expert games, and reinforcement learning from games of self-play. Without any lookahead search, the neural networks play Go at the level of state-of-the-art Monte-Carlo tree search programs that simulate thousands of random games of self-play. DeepMind also introduce a new search algorithm that combines Monte-Carlo simulation with value and policy networks. Using this search algorithm, our program AlphaGo achieved a 99.8% winning rate against other Go programs, and defeated the European Go champion by 5 games to 0. This is the first time that a computer program has defeated a human professional player in the full-sized game of Go, a feat previously thought to be at least a decade away.

Here you can read DeepMinds’s full paper on how AlphaGo works: deepmind-mastering-go.pdf.

In March 2016, AlphaGo will face its ultimate challenge: a 5-game challenge match in Seoul against the legendary Lee Sedol, the top Go player in the world over the past decade.

Here are a few videos about AlphaGo: