Golch

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[ Perceptron [1] Golch,

an experimental chess engine by Artem Pyatakov. Initially written in early 2001 [2] during his freshman year at Princeton University, it was a conventional chess program written in C, using a 0x88 board representation [3], alpha-beta, iterative deepening, transposition table [4], killer- and history heuristic, along with all the domain dependent tricks in move ordering (i.e searching captures first), selectivity and evaluation. In 2001, Golch was active at ICC [5]. The program was later used as test-bed for Pyatakov’s senior thesis Improving Computer Chess through Machine Learning [6] under advisor Robert Schapire [7]. The aim was to narrow the claimed gap between artificial intelligence methods and computer chess methods and tricks, manifested as human-generated, domain dependent ideas that happened to work without a good theoretical justification and cannot be easily generalized to other games [8].

Perceptron#

The online-learning approach to replace classical evaluation by a single layer perceptron, combining a feature vector, representing the board, with a set of adjustable weights, trained by supervised move adaption with some test-positions such as the Bratko-Kopec Test produced slightly disappointing results. The feature-vector used had 64 binary elements of an occupied bitboard, and a 16x16 attack map [9], which hopefully distinguished attacked but sufficiently defended pieces or pawns from pieces or pawns en prise.

History Heuristic#

More promising results was due to an advanced implementaion of history heuristic, where a table was not only indexed by its [from][to] coordinates of a move, but a much larger table with additional context of the moving piece along with a bitmask of pieces attacking the from square, which was reported to work about 3% better than the pure history heuristic in terms of node counts on the Bratko-Kopec problems [10]:

history[piece][from][to][attack_bit_vector] += (1 << depth);

See also#

• Chess Engines with Neural Networks
• Learning Chess Programs
• NeuroChess
• SAL

Publications#

• Artem Pyatakov (2004). Improving Computer Chess through Machine Learning. Senior thesis, Princeton University, advisor Robert Schapire [11]

Forum Posts#

• Fastest Conversion from 0x88 board to 8x8 board representation by Artem Pyatakov, CCC, July 06, 2001 » 0x88
• Question about Gerbil by Artem Pyatakov, CCC, July 11, 2001
• Bitfields and Crafty by Artem Pyatakov, CCC, July 11, 2001
• Artificial Intelligence in Computer Chess by Artem Pyatakov, CCC, March 28, 2004 » Artificial Intelligence
• Re: Artificial Intelligence in Computer Chess - *DETAILS* as promised by Artem Pyatakov, CCC, March 28, 2004 » History Heuristic
• Killer modifications reduced tree size by 8% (with identical results) by Artem Pyatakov, CCC, March 31, 2004 » Killer Heuristic

External Links#

• Finger golch at Internet Chess Club

References#

1. ↑ The appropriate weights are applied to the inputs, and the resulting weighted sum passed to a function that produces the output y, image created by mat_the_w, based on raster image Perceptron.gif by ‘ Paskari’, using Inkscape 0.46 for OSX, Wikimedia Commons, Perceptron from Wikipedia
2. ↑ Question about Gerbil by Artem Pyatakov, CCC, July 11, 2001
3. ↑ Fastest Conversion from 0x88 board to 8x8 board representation by Artem Pyatakov, CCC, July 06, 2001
4. ↑ Question about Gerbil by Artem Pyatakov, CCC, July 11, 2001
5. ↑ Finger golch at Internet Chess Club
6. ↑ Artificial Intelligence in Computer Chess by Artem Pyatakov, CCC, March 28, 2004
7. ↑ Princeton - Independent Project Presentation Schedule
8. ↑ Artificial Intelligence in Computer Chess by Artem Pyatakov, CCC, March 28, 2004
9. ↑ Re: Artificial Intelligence in Computer Chess - *DETAILS* as promised by Artem Pyatakov, CCC, March 28, 2004
10. ↑ Re: Artificial Intelligence in Computer Chess - *DETAILS* as promised by Artem Pyatakov, CCC, March 28, 2004
11. ↑ Artificial Intelligence in Computer Chess by Artem Pyatakov, CCC, March 28, 2004

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