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Ladder (Go)
In the game of Go, a ,() is a basic sequence of moves in which an attacker pursues a group in atari in a zig-zag pattern across the board. If there are no intervening stones, the group will hit the edge of the board and be captured. The sequence is so basic that there is a Go proverb saying "''if you don't know ladders, don't play Go.''" The ladder tactic fails if there are stones supporting those being chased close enough to the diagonal path of the ladder. Such a failing ladder is called a broken ladder. Secondary double threat tactics around ladders, involving playing a stone in such a way as to break the ladder and also create some other possibility, are potentially very complex. Such a play is called a ''ladder breaker''. A ladder can require reading 50 or more moves ahead, which even amateur players can do, as most of the moves are forced. Although ladders are one of the first techniques which human players learn, AlphaGo Zero was only able to handle them much later in its ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Go (board Game)
Go is an abstract strategy board game for two players in which the aim is to surround more territory than the opponent. The game was invented in China more than 2,500 years ago and is believed to be the oldest board game continuously played to the present day. A 2016 survey by the International Go Federation's 75 member nations found that there are over 46 million people worldwide who know how to play Go and over 20 million current players, the majority of whom live in East Asia. The playing pieces are called stones. One player uses the white stones and the other, black. The players take turns placing the stones on the vacant intersections (''points'') of a board. Once placed on the board, stones may not be moved, but stones are removed from the board if the stone (or group of stones) is surrounded by opposing stones on all orthogonally adjacent points, in which case the stone or group is ''captured''. The game proceeds until neither player wishes to make another move. When ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Atari (go)
Players of Go (board game), the game of Go often use jargon to describe situations on the board and surrounding the game. Such technical terms are likely to be encountered in books and articles about Go in English as well as other languages. Many of these terms have been borrowed from Japanese language, Japanese, mostly when no short equivalent English term could be found. This article gives an overview of the most important terms. Use of Japanese terms Although Go originated in China, the current English language, English and Western technical vocabulary borrows a high proportion of terms from the Japanese language because it was through Japan that the Western world, West was introduced to Go (game), Go. Many of these terms are from a jargon used for technical Go writing and are to some extent specially developed for Go journalism. Some authors of English-language Go materials avoid use of Japanese technical terms, and the way they are applied can differ in subtle ways from the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Go Proverb
Go, GO, G.O., or Go! may refer to: Arts and entertainment Games and sport * Go (game), a board game for two players * '' Travel Go'' (formerly ''Go – The International Travel Game''), a game based on world travel * Go, the starting position located at the corner of the board in the board game ''Monopoly'' * ''Go'', a 1992 game for the Philips CD-i video game system * ''Go'', a large straw battering ram used in the Korean sport of Gossaum * Go!, a label under which U.S. Gold published ZX Spectrum games * Go route, a pattern run in American football * ''Go'' series, a turn-based, puzzle video game series by Square Enix, based on various Square Enix franchises * '' Counter-Strike: Global Offensive'' (''CS:GO''), a first-person shooter developed by Valve * ''Pokémon Go'', an augmented reality game Film * ''Go'' (1999 film), American film * ''Go'' (2001 film), a Japanese film * ''Go'' (2007 film), a Bollywood film * ''Go Karts'' (film), an Australian film also titled as ''Go ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
AlphaGo Zero
AlphaGo Zero is a version of DeepMind's Go software AlphaGo. AlphaGo's team published an article in the journal ''Nature (journal), Nature'' on 19 October 2017, introducing AlphaGo Zero, a version created without using data from human games, and stronger than any previous version. By playing games against itself, AlphaGo Zero surpassed the strength of AlphaGo Lee in three days by winning 100 games to 0, reached the level of AlphaGo Master in 21 days, and exceeded all the old versions in 40 days. Training artificial intelligence (AI) without datasets derived from human experts has significant implications for the development of AI with superhuman skills because expert data is "often expensive, unreliable or simply unavailable." Demis Hassabis, the co-founder and CEO of DeepMind, said that AlphaGo Zero was so powerful because it was "no longer constrained by the limits of human knowledge". Furthermore, AlphaGo Zero performed better than standard reinforcement deep learning models (s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Nature (journal)
''Nature'' is a British weekly scientific journal founded and based in London, England. As a multidisciplinary publication, ''Nature'' features peer-reviewed research from a variety of academic disciplines, mainly in science and technology. It has core editorial offices across the United States, continental Europe, and Asia under the international scientific publishing company Springer Nature. ''Nature'' was one of the world's most cited scientific journals by the Science Edition of the 2019 ''Journal Citation Reports'' (with an ascribed impact factor of 42.778), making it one of the world's most-read and most prestigious academic journals. , it claimed an online readership of about three million unique readers per month. Founded in autumn 1869, ''Nature'' was first circulated by Norman Lockyer and Alexander Macmillan as a public forum for scientific innovations. The mid-20th century facilitated an editorial expansion for the journal; ''Nature'' redoubled its efforts in exp ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
AlphaGo
AlphaGo is a computer program that plays the board game Go (game), Go. It was developed by DeepMind Technologies a subsidiary of Google (now Alphabet Inc.). Subsequent versions of AlphaGo became increasingly powerful, including a version that competed under the name AlphaGo Master, Master. After retiring from competitive play, AlphaGo Master was succeeded by an even more powerful version known as AlphaGo Zero, which was completely Self-play (reinforcement learning technique), 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. AlphaGo and its successors use a Monte Carlo tree search algorithm to find its moves based on knowledge previously acquired by machine learning, specifically by an artificial neural network (a deep learning method) by extensi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
KataGo
KataGo is a free and open-source computer Go program, capable of defeating top-level human players. First released on 27 February 2019, it is developed by David Wu. Based on techniques used by DeepMind's AlphaGo Zero, KataGo implements Monte Carlo tree search with a convolutional neural network providing position evaluation and policy guidance. Compared to AlphaGo, KataGo introduces many refinements that enable it to learn faster and play more strongly. Notable features of KataGo that are absent in many other Go-playing programs include score estimation; support for small boards, arbitrary values of komi, and handicaps; and the ability to use various Go rulesets and adjust its play and evaluation for the small differences between them. KataGo's first release was trained by David Wu using resources provided by his employer Jane Street Capital, but it is now trained by a distributed effort. Members of the computer Go community provide computing resources by running the client, w ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Feature (machine Learning)
In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a phenomenon. Choosing informative, discriminating and independent features is a crucial element of effective algorithms in pattern recognition, classification and regression. Features are usually numeric, but structural features such as strings and graphs are used in syntactic pattern recognition. The concept of "feature" is related to that of explanatory variable used in statistical techniques such as linear regression. Classification A numeric feature can be conveniently described by a feature vector. One way to achieve binary classification is using a linear predictor function (related to the perceptron) with a feature vector as input. The method consists of calculating the scalar product between the feature vector and a vector of weights, qualifying those observations whose result exceeds a threshold. Algorithms for classification from a feature vector incl ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Neural Nets
Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons. An artificial neuron receives signals then processes them and can signal neurons connected to it. The "signal" at a connection is a real number, and the output of each neuron is computed by some non-linear function of the sum of its inputs. The connections are called ''edges''. Neurons and edges typically have a ''weight'' that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection. Neurons may have a threshold such that a signal is sent only if the aggregate signal crosses that threshold. Typically, n ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
