deeds_chess_system

[deeds]

hardware : dual xeon e5-2660v3
software : cutechess 1.2.0
settings : TC 60s+1s, 40 threads, hash 4096 MB, partial syzygy 7men

Opening list : Albert Silver's 25 gambit suit

Code: Select all

   # PLAYER                           :  RATING  ERROR  POINTS  PLAYED   (%)    W    D    L  D(%)  OppAvg  OppN
   1 Depth4_031222.exp (Eman 8.30)    :      42     70    28.0      50  56.0   10   36    4  72.0       0     1
   2 Mantis-DH1.bin (Eman 8.30)       :       0   ----    22.0      50  44.0    4   36   10  72.0      42     1

White advantage = 0.00 +/- 35.28
Draw rate (equal opponents) = 50.00 % +/- 0.00

link : games
pass : 59Ef9tOGT1RCBGYgpMTuzw

[deeds]

hardware : dual xeon e5-2660v3
software : cutechess 1.2.0
settings : TC 60s+1s, 40 threads, hash 4096 MB, partial syzygy 7men

Opening list : Jeroen Noomen's 50 tcec season 22 superfinal openings

Code: Select all

   # PLAYER                           :  RATING  ERROR  POINTS  PLAYED   (%)    W    D    L  D(%)  OppAvg  OppN
   1 Depth4_031222.exp (Eman 8.30)    :     105     54    63.5     100  63.5   29   69    2  69.0       0     1
   2 Mantis-DH1.bin (Eman 8.30)       :       0   ----    36.5     100  36.5    2   69   29  69.0     105     1

White advantage = 97.49 +/- 27.18
Draw rate (equal opponents) = 50.00 % +/- 0.00

link : games
pass : 59Ef9tOGT1RCBGYgpMTuzw

[deeds]

By grouping the engines with experience files VS the engines with opening book, we obtain this overall result :

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   # PLAYER                         :  RATING  ERROR  POINTS  PLAYED   (%)    W    D    L  D(%)  OppAvg  OppN
   1 experience_file (Eman 8.xx)    :      38     16   531.5     960  55.4  125  813   22  84.7       0     1
   2 opening_books (Eman 8.xx)      :       0   ----   428.5     960  44.6   22  813  125  84.7      38     1

White advantage = 23.30 +/- 8.00
Draw rate (equal opponents) = 50.00 % +/- 0.00

Some stats :

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experience_file (eman 8.xx) : avg. D32, 1 979 ms/move, 960 games, 50 394 moves
opening_books (eman 8.xx)   : avg. D34, 2 414 ms/move, 960 games, 40 917 moves

Averages :
207 sec/game (3 min/game)
113 plies/game (95 played plies/game)

[deeds]

How to read the moves of the games of the PGN files ?

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[Event "EXP VS BOOK"]
[Site "dual xeon e5-2660v3"]
[Date "2022.12.13"]
[Round "1"]
[White "Mantis-DH1 (Eman 8.30)"]
[Black "Depth4_031222 (Eman 8.30)"]
[Result "1/2-1/2"]
[ECO "B40"]
[GameDuration "00:01:54"]
[Opening "Sicilian"]
[PlyCount "44"]
[TimeControl "60+1"]
[Variation "Anderssen Variation"]

1. e4 {book} c5 {book} 2. Nf3 {book} e6 {book} 3. d4 {book} cxd4 {book}
4. Nxd4 {book} Nf6 {book} 5. Nc3 {book} d6 {book} 6. Be3 {book} Be7 {book}
7. g4 {book} h6 {book} 8. Qe2 Nc6 {+1.91/30 7.7s} 9. O-O-O Nxd4 {+1.89/23 0.58s}
10. Bxd4 {+2.04/33 9.6s} Bd7 {+1.87/28 1.5s} 11. f3 {+2.08/32 7.1s} Rc8 {+1.95/30 9.7s}
12. Qd2 {+2.10/32 6.2s} e5 {+1.94/27 3.9s} 13. Be3 {+2.00/32 6.3s} Qa5 {+1.87/29 5.1s}
14. a3 {+1.94/26 1.6s} a6 {+1.91/33 7.1s} 15. h4 {+2.05/29 7.4s} Be6 {+1.78/26 1.8s}
16. Be2 {+2.09/24 1.2s} b5 {+2.11/28 8.8s} 17. Kb1 g6 {+2.22/23 0.86s}
18. Rhe1 Rc6 {+1.90/26 4.7s} 19. Qd3 {+2.16/29 13s} Bc4 {+1.93/22 0.74s}
20. Qd2 {+2.19/27 1.1s} Be6 {+2.12/26 1.2s}
21. Rh1 {+2.19/29 2.2s} Rc8 {+1.90/25 1.2s}
22. Rhe1 Rc6 {0.00/45 1.1s, Draw by 3-fold repetition} 1/2-1/2

CUTECHESS-GUI adds the {book} mention after each move of the current opening.
For example : 1. e4 {book}...

When the engine plays a book's move, there is no evaluation.
For example : 8. Qe2 ...

When the engine is out-of-book, CUTECHESS-GUI adds the engine's evaluation.
For example : 10. Bxd4 {+2.04/33 9.6s} ...

CUTECHESS-GUI always adds the evaluation of the engine with experience data.
For example : ... Nc6 {+1.91/30 7.7s} ...

[deeds]

Why did you choose these 3 opening books (or these 3 book's authors) ?

As i knew nothing about the opening books nor their performance nor their rating, at the time i was inspired by the OCF rating list.
Then, i searched for the last available releases of the books from this rating list.
Starting from the best, at the time, i had found these ones.

[deeds]

Why did you choose a TC 1m+1s ?

It favors better the engine with the opening book, examples :
- with a TC 1m+1s, if the engine plays 30 book's moves, it increments its clock by 30s => +50% more time.
- with a TC 4m+2s, if the engine plays 30 book's moves, it increments its clock by 60s => +25% more time.

You should know that :
- in chess, the perfect game is a draw so the more time you give the engines the less difference there will be between them.
- even if the engine was trained with a TC 1m+1s on 7 threads, its learned experience data is really very resilient.

[deeds]

How was the experience file trained ?

Initially, i trained Eman on the openings where he had lost during my reference tournament (100 openings from salc_v3_10moves).
Then i trained Eman on the openings where the other engines did better (ex : eman drew when others won, eman lost when others drew, etc).

After each tournament, Eman analyzed its defeats at 10min/move then also the defeats of the other engines.

It's no longer a secret but learned data is better when an engine trains against several opponents because it faces different styles of play.
Since 2 years at 24/7 on few hosts, Eman trains until 4 sparring-partners who also have a learning feature so they don't repeat the same bad lines and try new ones.

[deeds]

What does reinforced experience data mean ?

reinforced = analyzed with greater depth / more time

When the engines train, they try several moves and depending on their efficiency, they forget them more or less quickly.
It generates some 'secondary' experience data which contains moves with shallow depth => imprecise evaluation.

In addition, depending on the TC and the threads number, the average depth is not very high so the resistance of the experience data is less important.

So it is necessary to reinforce this 'secondary' experience data by analyzing the moves which have a shallow depth.
For example, i analyzed at D40 all the moves of a hundred lines for each trained opening.
It improved the resilience of experience data.

[deeds]

hardware : dual xeon e5-2660v3
software : cutechess 1.2.0
settings : TC 60s+1s, 40 threads, hash 4096 MB, partial syzygy 7men

Opening list : GHPPN's 15 most popular openings

Code: Select all

   # PLAYER                :  RATING  ERROR  POINTS  PLAYED   (%)    W    D    L   D(%)  OppAvg  OppN
   1 deeds_chess_system    :       0   ----    15.0      30  50.0    0   30    0  100.0       0     1
   2 stockfish 15.1        :       0     92    15.0      30  50.0    0   30    0  100.0       0     1

White advantage = 0.00 +/- 46.89
Draw rate (equal opponents) = 50.00 % +/- 0.00

link : games
only for friends and family (request password and information by PM)

[deeds]

hardware : dual xeon e5-2660v3
software : cutechess 1.2.0
settings : TC 60s+1s, 40 threads, hash 4096 MB, partial syzygy 7men

Opening list : 20 first legal moves

Code: Select all

   # PLAYER                :  RATING  ERROR  POINTS  PLAYED   (%)    W    D    L  D(%)  OppAvg  OppN
   1 deeds_chess_system    :       0   ----    21.0      40  52.5    2   38    0  95.0     -18     1
   2 stockfish 15.1        :     -18     81    19.0      40  47.5    0   38    2  95.0       0     1

White advantage = -17.58 +/- 41.39
Draw rate (equal opponents) = 50.00 % +/- 0.00

link : games
only for friends and family (request password and information by PM)