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 their stones on the vacant intersections (points) on the board. Once placed, 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 a game concludes, the winner is determined by counting each player's surrounded territory along with captured stones and komi (points added to the score of the player with the white stones as compensation for playing second). Games may also end by resignation.
The standard Go board has a 19×19 grid of lines, containing 361 points. Beginners often play on smaller 9×9 and 13×13 boards, and archaeological evidence shows that the game was played in earlier centuries on a board with a 17×17 grid. Boards with a 19×19 grid had become standard, however, by the time the game reached Korea in the 5th century CE and Japan in the 7th century CE.
Go was considered one of the four essential arts of the cultured aristocratic Chinese scholars in antiquity. The earliest written reference to the game is generally recognized as the historical annal Zuo Zhuan (4th century BCE).
Despite its relatively simple rules, Go is extremely complex. Compared to chess, Go has both a larger board with more scope for play and longer games and, on average, many more alternatives to consider per move.
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Combinatorial game theory measures game complexity in several ways: State-space complexity (the number of legal game positions from the initial position), Game tree size (total number of possible games), Decision complexity (number of leaf nodes in the smallest decision tree for initial position), Game-tree complexity (number of leaf nodes in the smallest full-width decision tree for initial position), Computational complexity (asymptotic difficulty of a game as it grows arbitrarily large).
A strategy game or strategic game is a game (e.g. a board game) in which the players' uncoerced, and often autonomous, decision-making skills have a high significance in determining the outcome. Almost all strategy games require internal decision tree-style thinking, and typically very high situational awareness. Strategy games are also seen as a descendant of war games, and define strategy in terms of the context of war, but this is more partial.
Xiangqi (; ˈʃɑːŋtʃi), commonly known as Chinese chess or elephant chess, is a strategy board game for two players. It is the most popular board game in China. Xiangqi is in the same family of games as shogi, janggi, Western chess, chaturanga, and Indian chess. Besides China and areas with significant ethnic Chinese communities, this game is also a popular pastime in Vietnam, where it is known as cờ tướng, literally 'General's chess'. The game represents a battle between two armies, with the primary object being to checkmate the enemy's general (king).
Covers planning with adversaries, heuristic search algorithms, and strategies for games with chance, emphasizing the significance of deliberative agents.
Explores decision theory, risk functions, and inference in statistical analysis.
Ontological neighbourhood
:
:
:
We address online bandit learning of Nash equilibria in multi-agent convex games. We propose an algorithm whereby each agent uses only obtained values of her cost function at each joint played action, lacking any information of the functional form of her c ...
An online memory matching game is used to explore the collective performance for stimulus sets varying in color, text and texture. The game is a consistent five wide by four high array of 70 by 70 pixels squares for a total of eleven unique test pairs. Use ...
One prominent approach toward resolving the adversarial vulnerability of deep neural networks is the two-player zero-sum paradigm of adversarial training, in which predictors are trained against adversarially-chosen perturbations of data. Despite the promi ...