AlphaGo

AlphaGo is a computer program that plays the board game Go.wikipedia
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AlphaGo Zero

AlphaGo had three far more powerful successors, called AlphaGo Master, AlphaGo Zero and AlphaZero.
AlphaGo Zero is a version of DeepMind's Go software AlphaGo.

Computer Go

Gocomputer Go-playing systemcomputer to play Go
In October 2015, the original AlphaGo became the first computer Go program to beat a human professional Go player without handicaps on a full-sized 19×19 board.
The game of Go has been a fertile subject of artificial intelligence research for decades, culminating in 2017 with AlphaGo Master winning three of three games against Ke Jie, who at the time continuously held the world No.

DeepMind

Google DeepMindDeepMind TechnologiesAlphaStar
It was developed by DeepMind Technologies which was later acquired by Alphabet Inc.'s Google.
The company made headlines in 2016 after its AlphaGo program beat a human professional Go player Lee Sedol, the world champion, in a five-game match, which was the subject of a documentary film.

Lee Sedol

Lee Se-dol
In March 2016, it beat Lee Sedol in a five-game match, the first time a computer Go program has beaten a 9-dan professional without handicaps.
He was defeated by the computer program AlphaGo in a 1–4 series in March 2016.

Future of Go Summit

At the 2017 Future of Go Summit, its successor AlphaGo Master beat Ke Jie, the world No.1 ranked player at the time, in a three-game match (the even more powerful AlphaGo Zero already existed but was not yet announced).
It featured five Go games involving AlphaGo and top Chinese Go players, as well as a forum on the future of AI.

Ke Jie

At the 2017 Future of Go Summit, its successor AlphaGo Master beat Ke Jie, the world No.1 ranked player at the time, in a three-game match (the even more powerful AlphaGo Zero already existed but was not yet announced).
On 4 June 2016, at a news conference during the 37th World Amateur Go Championship, Yang Jun'an, the party chief of the Zhongguo Qiyuan and executive of the International Go Federation, revealed that the Google program AlphaGo would possibly have a match against Ke in the future.

Deep Blue versus Garry Kasparov

matchKasparov versus Deep Blue1996 match
Almost two decades after IBM's computer Deep Blue beat world chess champion Garry Kasparov in the 1997 match, the strongest Go programs using artificial intelligence techniques only reached about amateur 5-dan level, and still could not beat a professional Go player without handicaps.
Go programs were able to defeat only amateur players until 2015, when Google DeepMind's AlphaGo program surprisingly defeated Lee Sedol in the match AlphaGo versus Lee Sedol.

Artificial intelligence

AIA.I.artificially intelligent
Almost two decades after IBM's computer Deep Blue beat world chess champion Garry Kasparov in the 1997 match, the strongest Go programs using artificial intelligence techniques only reached about amateur 5-dan level, and still could not beat a professional Go player without handicaps.
In March 2016, AlphaGo won 4 out of 5 games of Go in a match with Go champion Lee Sedol, becoming the first computer Go-playing system to beat a professional Go player without handicaps.

Monte Carlo tree search

Monte-Carlo Tree SearchMCTSMonte Carlo tree-search algorithm
AlphaGo and its successors use a Monte Carlo tree search algorithm to find its moves based on knowledge previously "learned" by machine learning, specifically by an artificial neural network (a deep learning method) by extensive training, both from human and computer play. Facebook has also been working on its own Go-playing system darkforest, also based on combining machine learning and Monte Carlo tree search.
Google Deepmind developed the program AlphaGo, which in October 2015 became the first Computer Go program to beat a professional human Go player without handicaps on a full-sized 19x19 board.

Go (game)

Goweiqigame of Go
AlphaGo is a computer program that plays the board game Go.
In October 2015, Google DeepMind's program AlphaGo beat Fan Hui, the European Go champion and a 2 dan (out of 9 dan possible) professional, five times out of five with no handicap on a full size 19×19 board.

David Silver (computer scientist)

David SilverDavid Silver (programmer)
According to DeepMind's David Silver, the AlphaGo research project was formed around 2014 to test how well a neural network using deep learning can compete at Go.
Professor David Silver (dob c.1976) leads the reinforcement learning research group at DeepMind and was lead researcher on AlphaGo and co-lead on AlphaStar.

Fan Hui

Hui Fan
In October 2015, the distributed version of AlphaGo defeated the European Go champion Fan Hui, a 2-dan (out of 9 dan possible) professional, five to zero.
In October 2015, Fan was defeated by the Google DeepMind AI program AlphaGo 5–0, the first time an AI has beaten a human professional player at the game without a handicap.

Zen (software)

ZenDeepZenGoZenith Go
In 2012, the software program Zen, running on a four PC cluster, beat Masaki Takemiya (9p) two times at five and four stones handicap.
After the AlphaGo AI defeated professional players Fan Hui 2p and Lee Sedol 9p in 2015 and 2016, Yoji was inspired to upgrade Zen with deep learning algorithms.

AlphaGo versus Lee Sedol

a five-game matchAlphaGo LeeAlphaGo v. Lee Sedol
In March 2016, it beat Lee Sedol in a five-game match, the first time a computer Go program has beaten a 9-dan professional without handicaps.
AlphaGo versus Lee Sedol, also known as the Google DeepMind Challenge Match, was a five-game Go match between 18-time world champion Lee Sedol and AlphaGo, a computer Go program developed by Google DeepMind, played in Seoul, South Korea between the 9th and 15th of March 2016.

Aja Huang

After winning its 59th game Master revealed itself in the chatroom to be controlled by Dr. Aja Huang of the DeepMind team, then changed its nationality to the United Kingdom.
He works for DeepMind and was a member of the AlphaGo project.

Master (software)

AlphaGo MasterMaster
AlphaGo had three far more powerful successors, called AlphaGo Master, AlphaGo Zero and AlphaZero. At the 2017 Future of Go Summit, its successor AlphaGo Master beat Ke Jie, the world No.1 ranked player at the time, in a three-game match (the even more powerful AlphaGo Zero already existed but was not yet announced).
Master is a version of DeepMind's Go software AlphaGo, named after the account name (originally Magister/Magist) used online, which won 60 straight online games against human professional Go players from 29 December 2016 to 4 January 2017.

Deep Blue (chess computer)

Deep BlueIBM Deep BlueDeeper Blue
Almost two decades after IBM's computer Deep Blue beat world chess champion Garry Kasparov in the 1997 match, the strongest Go programs using artificial intelligence techniques only reached about amateur 5-dan level, and still could not beat a professional Go player without handicaps.

Tygem

On 29 December 2016, a new account on the Tygem server named "Magister" (shown as 'Magist' at the server's Chinese version) from South Korea began to play games with professional players.
In October 2015, AlphaGo from DeepMind beat the European Go champion Fan Hui five to zero.

AlphaGo versus Fan Hui

AlphaGo Fanfive times out of five
AlphaGo versus Fan Hui was a five-game Go match between European champion Fan Hui, a 2-dan (out of 9 dan possible) professional, and AlphaGo, a computer Go program developed by DeepMind, held at DeepMind's headquarters in London in October 2015.

Demis Hassabis

Dr. Demis Hassabis
After these games were completed, the co-founder of Google DeepMind, Demis Hassabis, said in a tweet, "we're looking forward to playing some official, full-length games later [2017] in collaboration with Go organizations and experts".
Since the Google acquisition, the company has notched up a number of significant achievements, perhaps the most notable being the creation of AlphaGo, a program that defeated world champion Lee Sedol at the complex game of Go.

Reinforcement learning

reward functionInverse reinforcement learningreinforcement
Once it had reached a certain degree of proficiency, it was trained further by being set to play large numbers of games against other instances of itself, using reinforcement learning to improve its play.
It has been applied successfully to various problems, including robot control, elevator scheduling, telecommunications, backgammon, checkers and Go (AlphaGo).

List of Go terms

hayagoataridivine move
In June 2016, at a presentation held at a university in the Netherlands, Aja Huang, one of the Deep Mind team, revealed that it had patched the logical weakness that occurred during the 4th game of the match between AlphaGo and Lee, and that after move 78 (which was dubbed the "divine move" by many professionals), it would play as intended and maintain Black's advantage.
Another good example is Lee Sedol vs AlphaGo on 13 March 2016 where Lee Sedol made white 78, a "wedge" play in the middle of the board, and it immediately turned the game around and defeated AlphaGo.

Artificial general intelligence

strong AIAIgeneral intelligence
When compared with Deep Blue or with Watson, AlphaGo's underlying algorithms are potentially more general-purpose, and may be evidence that the scientific community is making progress towards artificial general intelligence.

Darkforest

Facebook has also been working on its own Go-playing system darkforest, also based on combining machine learning and Monte Carlo tree search.
Google's AlphaGo program won against a professional player in October 2015 using a similar combination of techniques.