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Turochamp simulates a game of chess against the player by accepting the player's moves as input and outputting its move in response. The program's algorithm uses a heuristic to determine the best move to make, calculating all potential moves that it can make, then all of the potential player responses that could be made in turn, as well as further "considerable" moves, such as captures of ...
A position where white wins with optimal play, regardless of who has the next move The Lucena position is a position in chess endgame theory where one side has a rook and a pawn and the defender has a rook.
The faster the program produces cutoffs, the faster the search runs. The null-move heuristic is designed to guess cutoffs with less effort than would otherwise be required, whilst retaining a reasonable level of accuracy. The null-move heuristic is based on the fact that most reasonable chess moves improve the position for the side that played ...
An inline glossary of chess terms; A library of 500 famous games played by past world champions; An auxiliary graphical chessboard showing the computer's analysis while playing or reviewing moves; An interactive move list; An analysis text box, showing move's elapsed time, depth, score of the best evaluated line and number of positions seek
In competitive two-player games, the killer heuristic is a move-ordering method based on the observation that a strong move or small set of such moves in a particular position may be equally strong in similar positions at the same move (ply) in the game tree. Retaining such moves obviates the effort of rediscovering them in sibling nodes.
Before chess programs achieved master strength, and then became better than the best humans, adjournment was commonly offered in tournaments. When an adjournment is made, the player whose move it is secretly writes their next move on their scoresheet but does not make the move on the chessboard. Both opponents' scoresheets are then placed in ...
In computer chess, and in other games that computers play, late move reductions is a non-game-specific enhancement to the alpha–beta algorithm and its variants which attempts to examine a game search tree more efficiently. It uses the assumption that good game-specific move ordering causes a program to search the most likely moves early.
Darkforest uses a neural network to sort through the 10 100 board positions, and find the most powerful next move. [9] However, neural networks alone cannot match the level of good amateur players or the best search-based Go engines, and so Darkfores2 combines the neural network approach with a search-based machine.