Behind the contest, however, was important computer science, pushing forward the ability of computers to handle the kinds of complex calculations needed to help discover new medical drugs; do the broad financial modeling needed to identify trends and do risk analysis; handle large database searches; and perform massive calculations needed in many fields of science. The game is a collection of challenging problems for minds and machines, but has simple rules, and so is perfect for such experiments. IBM computer scientists had been interested in chess computing since the early s.
In , a graduate student at Carnegie Mellon University, Feng-hsiung Hsu, began working on his dissertation project: a chess playing machine he called ChipTest. A classmate of his, Murray Campbell, worked on the project, too, and in , both were hired to work at IBM Research. There, they continued their work with the help of other computer scientists, including Joe Hoane, Jerry Brody and C. The team named the project Deep Blue. The champion and computer met at the Equitable Center in New York, with cameras running, press in attendance and millions watching the outcome.
The odds of Deep Blue winning were not certain, but the science was solid.
The IBMers knew their machine could explore up to million possible chess positions per second. The chess grandmaster won the first game, Deep Blue took the next one, and the two players drew the three following games. Game 6 ended the match with a crushing defeat of the champion by Deep Blue. The match took place not on a standard stage, but rather in a small television studio. The audience watched the match on television screens in a basement theater in the building, several floors below where the match was actually held.
The theater seated about people, and was sold out for each of the six games.
The media attention given to Deep Blue resulted in more than three billion impressions around the world. When counting up the material for each side, typical values for pieces are 1 point for a pawn , 3 points for a knight or bishop , 5 points for a rook , and 9 points for a queen. See Chess piece relative value. By convention, a positive evaluation favors White, and a negative evaluation favors Black. In addition to points for pieces, most evaluation functions take many factors into account, such as pawn structure, the fact that a pair of bishops are usually worth more, centralized pieces are worth more, and so on.
The protection of kings is usually considered, as well as the phase of the game opening, middle or endgame. Endgame play had long been one of the great weaknesses of chess programs, because of the depth of search needed. Some otherwise master-level programs were unable to win in positions where even intermediate human players can force a win.
To solve this problem, computers have been used to analyze some chess endgame positions completely, starting with king and pawn against king. Such endgame tablebases are generated in advance using a form of retrograde analysis , starting with positions where the final result is known e.bpppbanyuwangi.com/cache/crisp/cywe-logiciel-pour-espionner.php
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Ken Thompson was a pioneer in this area. The results of the computer analysis sometimes surprised people. In Thompson's Belle chess machine used the endgame tablebase for a king and rook against king and queen and was able to draw that theoretically lost ending against several masters see Philidor position Queen versus rook.
This was despite not following the usual strategy to delay defeat by keeping the defending king and rook close together for as long as possible. Asked to explain the reasons behind some of the program's moves, Thompson was unable to do so beyond saying the program's database simply returned the best moves.
Most grandmasters declined to play against the computer in the queen versus rook endgame, but Walter Browne accepted the challenge. A queen versus rook position was set up in which the queen can win in thirty moves, with perfect play. After forty-five moves, Browne agreed to a draw, being unable to force checkmate or win the rook within the next five moves. In the final position, Browne was still seventeen moves away from checkmate, but not quite that far away from winning the rook.
In 1950, Alan Turing Created a Chess Computer Program That Prefigured A.I.
Browne studied the endgame, and played the computer again a week later in a different position in which the queen can win in thirty moves. Other positions, long believed to be won, turned out to take more moves against perfect play to actually win than were allowed by chess's fifty-move rule. As a consequence, for some years the official FIDE rules of chess were changed to extend the number of moves allowed in these endings. After a while, the rule reverted to fifty moves in all positions — more such positions were discovered, complicating the rule still further, and it made no difference in human play, as they could not play the positions perfectly.
Over the years, other endgame database formats have been released including the Edward Tablebase, the De Koning Database and the Nalimov Tablebase which is used by many chess programs such as Rybka , Shredder and Fritz. Tablebases for all positions with six pieces are available.
Many tablebases do not consider the fifty-move rule, under which a game where fifty moves pass without a capture or pawn move can be claimed to be a draw by either player. This results in the tablebase returning results such as "Forced mate in sixty-six moves" in some positions which would actually be drawn because of the fifty-move rule. One reason for this is that if the rules of chess were to be changed once more, giving more time to win such positions, it will not be necessary to regenerate all the tablebases.
It is also very easy for the program using the tablebases to notice and take account of this 'feature' and in any case if using an endgame tablebase will choose the move that leads to the quickest win even if it would fall foul of the fifty-move rule with perfect play. If playing an opponent not using a tablebase, such a choice will give good chances of winning within fifty moves. The Nalimov tablebases, which use state-of-the-art compression techniques, require 7. To cover all the six-piece endings requires approximately 1. It is estimated that a seven-piece tablebase requires between 50 and TB of storage space.
Endgame databases featured prominently in , when Kasparov played an exhibition match on the Internet against the rest of the world. A seven piece Queen and pawn endgame was reached with the World Team fighting to salvage a draw. Eugene Nalimov helped by generating the six piece ending tablebase where both sides had two Queens which was used heavily to aid analysis by both sides. Many other optimizations can be used to make chess-playing programs stronger.
For example, transposition tables are used to record positions that have been previously evaluated, to save recalculation of them. Refutation tables record key moves that "refute" what appears to be a good move; these are typically tried first in variant positions since a move that refutes one position is likely to refute another. Opening books aid computer programs by giving common openings that are considered good play and good ways to counter poor openings.
Many chess engines use pondering to increase their strength. Of course, faster hardware and additional processors can improve chess-playing program abilities, and some systems such as Deep Blue use specialized chess hardware instead of only software. Another way to examine more chess positions is to distribute the analysis of positions to many computers. The ChessBrain project  was a chess program that distributed the search tree computation through the Internet.
In the ChessBrain played chess using 2, computers. Chess engines have been developed to play some chess variants such as Capablanca Chess , but the engines are almost never directly integrated with specific hardware. Even for the software that has been developed, most will not play chess beyond a certain board size, so games played on an unbounded chessboard infinite chess remain virtually untouched by both chess computers and software.
These chess playing systems include custom hardware or run on supercomputers. In the s and early s, there was a competitive market for dedicated chess computers. This market changed in the mids when computers with dedicated processors could no longer compete with the fast processors in personal computers.
Nowadays, most dedicated units sold are of beginner and intermediate strength. Perhaps the most common type of chess software are programs that simply play chess. You make a move on the board, and the AI calculates and plays a response, and back and forth until one player resigns. Sometimes the chess engine , which calculates the moves, and the graphical user interface GUI are separate programs. A variety of engines can be imported into the GUI, so that you can play against different styles.
Engines often have just a simple text command-line interface while GUIs may offer a variety of piece sets, board styles or even 3D or animated pieces. Because recent engines are so strong, engines or GUIs may offer some way of limiting the engine's strength, so the player has a better chance of winning. Some versions of Fritz have a Handicap and Fun mode for limiting the current engine or changing the percentage of mistakes it makes or changing its style. Fritz also has a Friend Mode where during the game it tries to match the level of the player. Chess databases allow users to search through a large library of historical games, analyze them, check statistics, and draw up an opening repertoire.
Programs such as Playchess allow you to play games against other players over the internet. Chess training programs teach chess. Chessbase has Fritz and Chesster for children. There is also Software for handling chess problems. The prospects of completely solving chess are generally considered to be rather remote. It is widely conjectured that there is no computationally inexpensive method to solve chess even in the very weak sense of determining with certainty the value of the initial position, and hence the idea of solving chess in the stronger sense of obtaining a practically usable description of a strategy for perfect play for either side seems unrealistic today.
However, it has not been proven that no computationally cheap way of determining the best move in a chess position exists, nor even that a traditional alpha-beta-searcher running on present-day computing hardware could not solve the initial position in an acceptable amount of time.
The difficulty in proving the latter lies in the fact that, while the number of board positions that could happen in the course of a chess game is huge on the order of at least 10 43  to 10 47 , it is hard to rule out with mathematical certainty the possibility that the initial position allows either side to force a mate or a threefold repetition after relatively few moves, in which case the search tree might encompass only a very small subset of the set of possible positions.
It has been mathematically proven that generalized chess chess played with an arbitrarily large number of pieces on an arbitrarily large chessboard is EXPTIME-complete ,  meaning that determining the winning side in an arbitrary position of generalized chess provably takes exponential time in the worst case; however, this theoretical result gives no lower bound on the amount of work required to solve ordinary 8x8 chess. Progress has also been made from the other side: as of , all 7 and fewer piece 2 kings and up to 5 other pieces endgames have been solved. A "chess engine" is software that calculates and orders which moves are the strongest to play in a given position.
Engine authors focus on improving the play of their engines, often just importing the engine into a graphical user interface GUI developed by someone else. Chessbase has its own proprietary protocol, and at one time Millennium had another protocol used for ChessGenius. Engines designed for one operating system and protocol may be ported to other OS's or protocols. In , the Internet Chess Club released its first Java client for playing chess online against other people inside one's webbrowser.
Free Internet Chess Server followed soon after with a similar client. Another popular web app is tactics training. The now defunct Chess Tactics Server opened its site in ,  followed by Chesstempo the next year,  and Chess. Chessbase took their chess game database online in One could play against the engine Shredder online from Starting in , Chess.
From Wikipedia, the free encyclopedia. Main article: Human-computer chess matches. Deep Blue vs. Kasparov, , game 1. Main article: Board representation chess. Main article: Endgame tablebase. Main article: Solving chess. Main article: Chess engine. The repeating time control means that the time is reset after each multiple of this number of moves is reached. Bowden, Pitman, London Archived from the original on 21 July Retrieved 1 December ICGA Journal.
Retrieved 17 October January Retrieved 18 October Your Computer. British Chess Magazine. He also mentions using both in John Nunn. Nunn's Best Games. Garry Kasparov's Fighting Chess. Henry Holt.
New In Chess. Archived from the original on Retrieved Chessbase News. Retrieved 19 February Infinity Chess. Innovative Solutions. Retrieved 20 April New Scientist. Retrieved 22 January Operations Research.
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Deutsche Welle. Retrieved 26 August October Retrieved 25 September Robert Hyatt's home page". See Shannon number for details. Theory Ser. A , 31 2 : —, doi : List of openings theory table List of chess gambits Irregular Quick checkmates Fool's mate Scholar's mate. Bishop and knight checkmate King and pawn vs king Opposite-coloured bishops Pawnless endgame Queen and pawn vs queen Queen vs pawn Rook and bishop vs rook Rook and pawn vs rook Lucena position Philidor position Strategy fortress opposition Tarrasch rule triangulation Zugzwang Study Tablebase Two knights endgame Wrong bishop Wrong rook pawn.
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