Computer Chess - Recent Developments, Support Systems, Programs - Literature review Example

Literature Review of Computer Chess Abstract With the number of people interested in chess game around the world increasing and the game gaining popularity, the importance of having developed chess game systems in place is a major concern in the industry. Innovations to computer chess are becoming open-ended and demand for the same is on the increase. Not many studies have been devoted to identifying computer chess but efforts in the 21st century are on a high. This paper will examine the developments of computer chess highlighted and discussed to give an overview on the topic. Introduction The idea to develop a chess-playing machine dates back early in the eighteenth century. Around late 1769, the chess-playing automaton named The Turk became hugely famous before exposed as being a hoax. Before the original development of digital computing, many serious trials basing on automata for instance El Ajedrecista of 1912 developed too complex and limited programs. They could not be useful effectively for playing full games of computer chess (Dylan 2006; Robinson 1999, p. 1396-1398). The field of mechanical chess research fades away until the advent of the late century digital computer in the early 1950s. Since then, chess enthusiasts as well as computer engineers build the programs with increasing degrees of success including chess-playing machines and programs. This paper is a literature review of computer chess detailing relevant information on the game and its development in the computer world. Main body Computer chess definition Computer chess refers to computer architecture, which encompasses hardware and software making it possible to play chess autonomously precisely without human guidance (Dylan 2006; Robinson 1999, p. 1396-1398). Computer chess generally occurs as solo entertainment, which allows players to practice as well as amuse themselves especially when there are no human opponent available (Dirk 2000, p. 1385-1389; Bruce 2004, p. 442-447; Hsu 2002, p.15). Computer chess acts also as aids to chess analysis, as research providing insights to human cognition and for competitions in computer chess. Computer chess recent developments Chess-playing computers are currently accessible to the average consumer. From early 70's to date, dedicated chess computers available for purchase have been many. There are several chess engines for instance Fruit, Crafty, and GNU Chess, which are downloadable directly from the Internet at least free (Stiller 1996; Monroe 1989, p. 197-250). These engines are particularly able to play a chess game that, when run particularly on an up-to-date personal computer, they defeat most master players in tournament conditions (Robinson 1999, p. 1396-1398). Top programs for instance the closed-source programs Fritz or Shredder or the open source Stockfish program have surpassed many world champion players at blitz as well as short time controls. As of late 2008 in October, Rybka a top-rated in CCRL, CSS, SSDF, CEGT and WBEC rating has won many computer chess tournaments recently such as 2006 Dutch Open Championship, CCT 8 and 9, the 15th World Championship and the 16th IPCCC (Bruce 2004, p. 442-447; Hsu 2002, p.15; Barbara 1998). The developers of a computer chess system is a combination of a number of basic implementation issues (Newborn 2006; Monroe 1989, p. 197-250). They include Board representation (the representation of a single position in data structures), Search techniques (the identification of possible moves and the selection of the highly promising ones for later examination) and Leaf evaluation (the evaluation of a board position value). Computer chess support systems Computer chess programs typically support a number of ordinary de facto standards. Nearly all of the computer chess programs today can read and write respective game moves for instance Portable Game Notation (PGN). They can also read and write positions for instance Forsyth-Edwards Notation (FEN). Older chess computer programs often only recognized long algebraic notation, but the current users expect chess programs to be acquainted with standard algebraic chess notation (Hsu 2002, p.15; Barbara 1998). Most computer programs for chess have divisions into an engine (which generally computes the move given a present position) as well as the user interface. Most engines are precisely separate programs from the respective user interface, and the overall two parts communicate directly with each other and use a public communication protocol (Dylan 2006; Robinson 1999, p. 1396-1398). Chess Engine Communication is the popular protocol in computer chess. The Universal Chess Interface Another open is substitute chess, communication protocol. With the division of chess programs into the two pieces, the program developers can write precisely only the user interface or the engine only, without having to write the two parts of the program (Stiller 1996; Newborn 2006; Monroe 1989, p. 197-250). Implementers of the program need to decide if they use endgame databases or any other optimizations of the programs, and often apply common de facto standards (Bruce 2004, p. 442-447; Hsu 2002, p.15; Barbara 1998). Computer chess programs Shannon published the first paper particularly on the subject late in 1950 before anyone developed a computer chess program. He predicted successfully the two main possible search strategies that would be of use in computer chess development labeled as "Type A" and "Type B". Type A programs would particularly use a "brute force" approach; examine every possible position for a respective fixed number of moves with the use of the minim max algorithm. However, Shannon believed that this would not be practical for two weighty reasons (Dylan 2006; Robinson 1999, p. 1396-1398). First, with an approximated thirty moves in a typical real-life position, it would be the expectation that to search the 109 positions involved to look for three moves ahead for respective sides (six plies) would literally take an approximated sixteen minutes (Dirk 2000, p. 1385-1389; Barbara 1998). Secondly, it ignored the quiescence problem, trying to evaluate only a position at the end of a piece's exchange or relatively other significant sequence of moves ('lines'). "Type B" programs would be of use with two main improvements including employed quiescence search and looking only at a few perfect moves for respective positions (Bruce 2004, p. 442-447; Hsu 2002, p.15; Barbara 1998). The problem with computer chess type B is that it would rely on the program deciding, which moves are powerful enough to be considered ('plausible') in any respective position and this proved much harder of a problem to solve than trying to speed up type A, searches using superior hardware as well as search extension techniques (Stiller 1996). Chess grandmasters have devoted themselves seriously to computer chess with examples of former World Champion in chess competition, Mikhail. He who wrote several works on computer chess (Monroe 1989, p. 197-250). Mikhail worked with relatively primitive hardware, which was available in the Soviet Union early in the 1960s giving him no choice but investigate software selection techniques. In 1965 Mikhail was a consultant to the ITEP team established in a US-Soviet computer chess match that led to the initial development of computer chess (Dylan 2006; Robinson 1999, p. 1396-1398). One developmental milestone for computer chess was when the Northwestern University team, which was responsible particularly for the Chess series of programs winning the first three ACM Championships (1970–72), did not use type B searching late in 1973 championships. The resulting program for computer chess was Chess 4.0, which won the ear's championship. Type B was stressful during competition, which is why 4.0 were of use because it was tricky to anticipate the moves their type B programs played, and why. The innovators reported that type A of the computer chess was much easier to debugging in the four months they used it therefore would be excellent when upgraded (Monroe 1989, p. 197-250). Computer chess operations Computer chess programs mull over chess moves as a type of game tree. In theory, they examine literally all moves, then all the played counter-moves to the respective moves, and then all moves played to counter them, and so on (Dylan 2006; Robinson 1999, p. 1396-1398). Each individual move by a single player is called a "ply". The evaluation continues up to a certain search depth or the computer chess program determines that a final "leaf" position is reached for instance checkmate). For many chess positions, computer chess cannot look ahead to at least all final possible positions. As an alternative, they must look ahead at least to a few plies and evaluate particularly the final board position (Monroe 1989, p. 197-250). The algorithm, which evaluates final board positions, is "evaluation function", and the algorithms are vastly different often between different computer chess programs (Dirk 2000, p. 1385-1389; Bruce 2004, p. 442-447; Hsu 2002, p.15; Barbara 1998). Evaluation functions characteristically evaluate positions in precisely hundredths of a pawn, and consider the exact material value along with factors that affect the strength of each side (Monroe 1989, p. 197-250). In the event of counting, the exact material for each respective side, archetypal values for pieces are 1 point (a pawn), 3 points (a bishop or knight), 5 points (a rook), and 9 points (a queen) (Dylan 2006; Robinson 1999, p. 1396-1398). By convention, a relative positive evaluation is always in favor of a White, and a precisely negative evaluation is for the Black. In computer chess, the king is granted sometimes an arbitrary high value for instance 200 points or 1,000,000,000 points ensuring that a checkmate generally outweighs the other factors. Evaluation functions often take several factors into account, for instance pawn structure (Monroe 1989, p. 197-250). Conclusion Computer chess has evolved over years and it is taking the market by surprise. These programs are particularly able to play a chess game that, when run particularly on an up-to-date personal computer, they defeat most master players in tournament conditions (Dylan 2006; Robinson 1999, p. 1396-1398). There has been less information regarding computer chess because many people are not aware of the classic game of chess played through computers, however, the less available is relevant for this literature review in analyzing computer chess as a game in the 21st century. References Barbara, J 1998, A program to play chess end games, Stanford University Department of Computer Science, Technical Report CS 106, Stanford Artificial Intelligence Project Memo AI-65 Bruce, D 2004, “The Effects of Speed on Skilled Chess Performance” Psychological Science, Vol. 15, No. 7 (Jul., 2004), pp. 442-447 Dirk, F 2000, “Molecular Computation: RNA Solutions to Chess Problem” Proceedings of the National Academy of Sciences of the United States of America, Vol. 97, No. 4 (Feb. 15, 2000), pp. 1385-1389 Dylan, L 2006, “Once Again, Machine Beats Human Champion at Chess” New York Times, from, http://www.nytimes.com/2006/12/05/crosswords/chess/05cnd-chess.html?_r=1 Hans, J 1998, “A chronology of computer chess and its literature” Artificial Intelligence, Volume 10, Issue 2, April 1998, p. 201-214 Hsu, F 2002, Behind Deep Blue: Building the Computer that Defeated the World Chess Champion, Princeton University Press, p.15 Monroe, M 1989, “Computer Chess: Ten Years of Significant Progress” Advances in Computers, Volume 29, 1989, Pages 197-250 Monroe, M 2008, “Recent Progress in Computer Chess” Advances in Computers, Volume 18, 1979, p. 59-117. Newborn, M 2006, Theo and Octopus at the 2006 World Championship for Automated Reasoning Programs, Seattle, Washington, August 18, 2006 Robinson, L 1999, “Tournament Competition Fuels Computer Chess”, Science, New Series, Vol. 204, No. 4400 (Jun. 29, 1999), pp. 1396-1398 Stiller, L 1996, “Multi linear Algebra and Chess Endgames”, Berkeley, California: Mathematical Sciences Research Institute, Games of No Chance, MSRI Publications, Volume 29, http://www.msri.org/publications/books/Book29/files/stiller.pdf, retrieved 21 June 2009 Read More