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KnightCap
Original author(s)
Andrew Tridgell
Written in
C
Platform
Unix
Type
Chess engine
License
GNU General Public License
Website
www.samba.org/KnightCap/
This article is part of the series on
Chess programming
Board representations
0x88
Bitboards
Evaluation functions
Deep neural networks (Transformers)
Attention
Efficiently updatable neural networks
Handcrafted evaluation functions
Piece-square tables
Reinforcement learning
Stochastic gradient descent
Supervised learning
Texel tuning
Unsupervised learning
Graph and tree search algorithms
Minimax
Alpha-beta pruning
Principal variation search
Quiescence search
Monte Carlo tree search
Chess computers
Belle
ChessMachine
ChipTest
Cray Blitz
Deep Blue
Deep Thought
HiTech
Hydra
Mephisto
Saitek
Chess engines
AlphaZero
Chess Tiger
Crafty
CuckooChess
Deep Fritz
Dragon by Komodo Chess
Fairy-Max
Fritz
Fruit
GNU Chess
HIARCS
Houdini
Ikarus
Junior
KnightCap
Komodo
Leela Chess Zero
MChess Pro
Mittens
MuZero
Naum
REBEL
Rybka
Shredder
Sjeng
SmarThink
Stockfish
Torch
Turochamp
Zappa
v
t
e
KnightCap is an open source computer chess engine. Its primary author is Andrew Tridgell and it was created circa 1996. Major contributions have also been made by Jon Baxter and probably minor contributions by a few others. KnightCap is free software released under the GNU General Public License (GPL).
In most ways, KnightCap is a fairly typical modern program. It uses bitboard data structures that are slightly different from those that were well known in 1996, but obvious enough and probably well known now. There is backward pruning using MTD(f) (a method approximately equivalent to Alpha-beta pruning but slightly more efficient in some settings). There is Null-move heuristic. There is a fairly complex end-node evaluation process that considers similar features to other programs.
In addition, KnightCap has support for multi-processor computers, in particular the now obsolete Fujitsu CAP computer
research machines.
The most original feature of KnightCap, introduced in the late 1990s, was an experiment in temporal difference learning as applied to chess. This technique allowed KnightCap to automatically tune the weights applied to the various features in its evaluation function based on the games it played.
For a while in the 1990s, KnightCap was quite active on chess servers on the Internet, but it is now semi-retired and rarely seen. Its strength is below that of the strongest programs, but still quite good.[citation needed]
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