This glossary of chess explains commonly used terms in chess, in alphabetical order. Some of these terms have their own pages, like fork and pin. For a list of unorthodox chess pieces, see Fairy chess piece; for a list of terms specific to chess problems, see Glossary of chess problems; for a list of named opening lines, see List of chess openings; for a list of chess-related games, see List of chess variants; for a list of terms general to board games, see Glossary of board games.
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An endgame tablebase is a computerized database that contains precalculated exhaustive analysis of chess endgame positions. It is typically used by a computer chess engine during play, or by a human or computer that is retrospectively analysing a game that has already been played. The tablebase contains the game-theoretical value (win, loss, or draw) in each possible position, and how many moves it would take to achieve that result with perfect play. Thus, the tablebase acts as an oracle, always providing the optimal moves.
Online chess is chess that is played over the Internet, allowing players to play against each other in real time. This is done through the use of Internet chess servers, which often include a system to pair up individual players based on their rating using an Elo or similar chess rating system. Online chess has existed since the 1970s, but has seen a rapid growth in popularity amidst the COVID-19 pandemic and rise of chess livestreaming. Online chess has existed in various forms including PLATO and play-by-email since the dawn of the Internet in the 1970s.
Computer chess includes both hardware (dedicated computers) and software capable of playing chess. Computer chess provides opportunities for players to practice even in the absence of human opponents, and also provides opportunities for analysis, entertainment and training. Computer chess applications that play at the level of a chess master or higher are available on hardware from supercomputers to smart phones. Standalone chess-playing machines are also available.
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Reinforcement learning is a type of supervised learning, where reward is sparse and delayed. For example in chess, a series of moves is made until a sparse reward (win, loss) is issued, which makes it impossible to evaluate the value of a single move. Stil ...