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AlphaGo is a computer program that plays the board game Go. It was developed by the London-based DeepMind Technologies, an acquired subsidiary of Google (now Alphabet Inc.). Subsequent versions of AlphaGo became increasingly powerful, including a version that competed under the name Master. After retiring from competitive play, AlphaGo Master was succeeded by an even more powerful version known as AlphaGo Zero, which was completely self-taught without learning from human games. AlphaGo Zero was then generalized into a program known as AlphaZero, which played additional games, including chess and shogi. AlphaZero has in turn been succeeded by a program known as MuZero which learns without being taught the rules. (Full article...)

The dan (段) ranking system is used by many Japanese, Okinawan, Korean, and other martial arts organizations to indicate the level of a person's ability within a given system. Used as a ranking system to quantify skill level in a specific domain, it was originally used at a Go school during the Edo period. It is now also used in most modern Japanese fine and martial arts. (Full article...)

In computer science, Monte Carlo tree search (MCTS) is a heuristic search algorithm for some kinds of decision processes, most notably those employed in software that plays board games. In that context MCTS is used to solve the game tree. (Full article...)

AlphaZero is a computer program developed by artificial intelligence research company DeepMind to master the games of chess, shogi and go. This algorithm uses an approach similar to AlphaGo Zero. (Full article...)

The rules of Go have seen some variation over time and from place to place. This article discusses those sets of rules broadly similar to the ones currently in use in East Asia. Even among these, there is a degree of variation. (Full article...)

Hikaru no Go (ヒカルの碁, lit. Hikaru's Go) is a Japanese manga series based on the board game Go, written by Yumi Hotta and illustrated by Takeshi Obata. The production of the series' Go games was supervised by Go professional Yukari Umezawa. It was serialized in Shueisha's Weekly Shōnen Jump from 1998 to 2003, with its chapters collected into 23 tankōbon volumes. The story follows Hikaru, who discovers a Go board in his grandfather's attic one day. The object turns out to be haunted by a ghost named Sai, the emperor's former Go teacher in the Heian era. Sai finds himself trapped in Hikaru's mind and tells him which moves to play against opponents, astonishing onlookers with the boy's apparent level of skill at the game. (Full article...)

AlphaGo versus Lee Sedol, also known as the DeepMind Challenge Match, was a five-game Go match between top Go player Lee Sedol and AlphaGo, a computer Go program developed by DeepMind, played in Seoul, South Korea between 9 and 15 March 2016. AlphaGo won all but the fourth game; all games were won by resignation. The match has been compared with the historic chess match between Deep Blue and Garry Kasparov in 1997. (Full article...)

Lee Sedol (Korean: 이세돌; born 2 March 1983), or Lee Se-dol, is a former South Korean professional Go player of 9 dan rank. As of February 2016, he ranked second in international titles (18), behind only Lee Chang-ho (21). His nickname is "The Strong Stone" ("Ssen-dol"). In March 2016, he played a notable series of matches against the program AlphaGo that ended in Lee losing 1–4. (Full article...)

There are various systems of Go ranks and ratings that measure the skill in the traditional board game Go. Traditionally, Go rankings have been measured using a system of dan and kyu ranks. Especially in amateur play, these ranks facilitate the handicapping system, with a difference of one rank roughly corresponding to one free move at the beginning of the game. This system is also commonly used in many East Asian martial arts, where it often corresponds with a belt color. With the ready availability of calculators and computers, rating systems have been introduced. In such systems, a rating is rigorously calculated on the basis of game results. (Full article...)