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New version chess engines: Polyfish 20230410, ShashChess 31.1, BrainLearn 23.1 NNUE

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Polyfish is a UCI chess engine based on Stockfish. Rating CEDR=3726
It is identical to Stockfish with the added capability of handling Polyglot,

Polyfish supports two polyglot BIN books at the same time. The second book is only probed if the first book has no moves for the given position. The engine starts searching only if no move is found in either the first book or the second book.

Individual statistics: Polyfish 230202 - 312 games (+ 87,=224,-  1), 63.8   %
Critter 1.6a                  :   8 (+  7,=  1,-  0), 93.8 %
SugaR AI 2.50                 :   1 (+  1,=  0,-  0), 100.0 %
Komodo 13.02                  :   2 (+  1,=  1,-  0), 75.0 %
RofChade 3.0                  :   2 (+  1,=  1,-  0), 75.0 %
StockfishMZ 170522            :   2 (+  0,=  2,-  0), 50.0 %
Fisherov chess monk 1.2       :  12 (+  0,= 12,-  0), 50.0 %
Demolito 2021-10-21           :   2 (+  2,=  0,-  0), 100.0 %
Revenge 3.0                   :   6 (+  4,=  2,-  0), 83.3 %
Teal Oracle                   :   1 (+  1,=  0,-  0), 100.0 %
Nebula-vortex 1.0             :   1 (+  0,=  1,-  0), 50.0 %
DarkSister 1.9a               :   1 (+  0,=  1,-  0), 50.0 %
Berserk 10                    :   2 (+  1,=  1,-  0), 75.0 %
AI 27.0                       :   1 (+  0,=  1,-  0), 50.0 %
YuliGM PrO 4.0                :   1 (+  0,=  1,-  0), 50.0 %
Seer 2.6                      :   2 (+  2,=  0,-  0), 100.0 %
Kayra 1.7                     :  10 (+  0,= 10,-  0), 50.0 %
Cool Iris 5.2                 :   1 (+  0,=  1,-  0), 50.0 %
RubiChess 20221203            :   2 (+  0,=  2,-  0), 50.0 %
Cheese 3.1.1                  :   2 (+  2,=  0,-  0), 100.0 %
Kookaburra 1.03a              :  10 (+  0,= 10,-  0), 50.0 %
Little Goliath 3.16           :   2 (+  2,=  0,-  0), 100.0 %
Dragon 3.2                    :  10 (+  2,=  8,-  0), 60.0 %
Uralochka 3.39d               :   2 (+  1,=  1,-  0), 75.0 %
Rebel 16.1                    :   2 (+  1,=  1,-  0), 75.0 %
Blue Marlin 15.6              :  11 (+  1,= 10,-  0), 54.5 %
BrainLearn 21.1               :  10 (+  0,=  9,-  1), 45.0 %
Koivisto 9.0                  :   2 (+  0,=  2,-  0), 50.0 %
Koivisto 9.0 Ipman            :   2 (+  1,=  1,-  0), 75.0 %
Stockfish 20230125            :   6 (+  0,=  6,-  0), 50.0 %
Corchess 230125               :   2 (+  0,=  2,-  0), 50.0 %
Viridithas 7.0.0              :   7 (+  6,=  1,-  0), 92.9 %
Protej 0.6.4                  :   6 (+  6,=  0,-  0), 100.0 %
BlackCore 5.1                 :   6 (+  5,=  1,-  0), 91.7 %
Vafra 12.3 Cfish              :   6 (+  2,=  4,-  0), 66.7 %
CorChess 20230125             :   4 (+  0,=  4,-  0), 50.0 %
Winter 2.0                    :   6 (+  6,=  0,-  0), 100.0 %
Eman 8.70                     :  17 (+  0,= 17,-  0), 50.0 %
Igel 3.4.0                    :   8 (+  2,=  6,-  0), 62.5 %
Stockfish 20230202            :   4 (+  0,=  4,-  0), 50.0 %
ShashChess 28                 :  16 (+  0,= 16,-  0), 50.0 %
Smallbrain 7.0                :   6 (+  2,=  4,-  0), 66.7 %
Charisma Light 2              :   6 (+  0,=  6,-  0), 50.0 %
RukChess 3.0.15 NNUE2         :   2 (+  2,=  0,-  0), 100.0 %
Stockfish 230202              :   2 (+  0,=  2,-  0), 50.0 %
Stockfish 230125 Ivec         :   2 (+  0,=  2,-  0), 50.0 %
Bagatur 3.7                   :   2 (+  2,=  0,-  0), 100.0 %
Mess 0.1.0                    :   2 (+  2,=  0,-  0), 100.0 %
Koivisto 9.2 hotfix           :   2 (+  1,=  1,-  0), 75.0 %
CorChess 20230210             :   4 (+  0,=  4,-  0), 50.0 %
Caissa 1.6                    :   2 (+  2,=  0,-  0), 100.0 %
Predator X5                   :   2 (+  0,=  2,-  0), 50.0 %
Stockfish 20230203            :   2 (+  0,=  2,-  0), 50.0 %
Velvet 5.1.0                  :   2 (+  2,=  0,-  0), 100.0 %
Fat Fritz 2                   :  10 (+  3,=  7,-  0), 65.0 %
Patzer AI 020223              :   4 (+  0,=  4,-  0), 50.0 %
Berserk 11                    :   2 (+  0,=  2,-  0), 50.0 %
Clover 3.3.1                  :   2 (+  2,=  0,-  0), 100.0 %
Caissa 1.6.3                  :   2 (+  2,=  0,-  0), 100.0 %
Rebel 16.2                    :  10 (+  2,=  8,-  0), 60.0 %
Stockfish 20230218            :   6 (+  0,=  6,-  0), 50.0 %
Berserk 11.1                  :   8 (+  3,=  5,-  0), 68.8 %
Koivisto 9.2                  :  10 (+  3,=  7,-  0), 65.0 %
Charisma Blitz                :   2 (+  0,=  2,-  0), 50.0 %
Ethereal 14.00 NNUE           :  10 (+  1,=  9,-  0), 55.0 %
Charisma 250223               :   8 (+  1,=  7,-  0), 56.2 %
CorChess 20230226             :   4 (+  0,=  4,-  0), 50.0 %


github:https://github.com/khalid-a-omar/Polyfish/releases/tag/20230410





ShashChess - UCI chess engine.
Rating CEDR=3720 (01.04.2023)

ShashChess is a free UCI chess engine derived from Stockfish family chess engines. 

v.31.1:
Again refined Shashin theory
Updated and very refined testsuite
Stockfish patch
Apr 7, 2023
Depth Tweak and tuning
tunes reduction related parameters, and introduces more reduction on found good moves.
credit for this patch goes also to candirufish Yoshie2000 dubslow peregrineshahin Vizvezdenec

Individual statistics: ShashChess 28 - 504 games (+133,=365,-  6), 62.6 %
Critter 1.6a                  :   6 (+  5,=  1,-  0), 91.7 %
Komodo 13.02                  :   2 (+  2,=  0,-  0), 100.0 %
RofChade 3.0                  :   8 (+  3,=  5,-  0), 68.8 %
SlowChess 2.9                 :   8 (+  2,=  6,-  0), 62.5 %
Fisherov chess monk 1.2       :  22 (+  1,= 19,-  2), 47.7 %
Demolito 2021-10-21           :   2 (+  2,=  0,-  0), 100.0 %
Revenge 3.0                   :  14 (+  2,= 12,-  0), 57.1 %
Booot 7.0                     :   2 (+  2,=  0,-  0), 100.0 %
Seer 2.6                      :   8 (+  5,=  3,-  0), 81.2 %
Kayra 1.7                     :  18 (+  0,= 18,-  0), 50.0 %
Berserk 20221129              :   2 (+  1,=  1,-  0), 75.0 %
Stockfish 15.1                :  18 (+  0,= 18,-  0), 50.0 %
RubiChess 20221203            :   8 (+  3,=  5,-  0), 68.8 %
Cheese 3.1.1                  :   2 (+  2,=  0,-  0), 100.0 %
Kookaburra 1.03a              :  18 (+  0,= 18,-  0), 50.0 %
Little Goliath 3.16           :   2 (+  2,=  0,-  0), 100.0 %
Dragon 3.2                    :  20 (+  1,= 19,-  0), 52.5 %
Velvet 5.0.0                  :   4 (+  3,=  1,-  0), 87.5 %
Minic 3.33                    :   4 (+  2,=  2,-  0), 75.0 %
Uralochka 3.39d               :  10 (+  7,=  3,-  0), 85.0 %
Rebel 16.1                    :   6 (+  4,=  2,-  0), 83.3 %
Eman 8.60                     :   4 (+  0,=  4,-  0), 50.0 %
Blue Marlin 15.6              :  18 (+  0,= 18,-  0), 50.0 %
BrainLearn 21.1               :  18 (+  2,= 16,-  0), 55.6 %
Koivisto 9.0                  :   4 (+  2,=  2,-  0), 75.0 %
Polyfish 230115               :   4 (+  0,=  4,-  0), 50.0 %
Caissa 1.5                    :   4 (+  2,=  2,-  0), 75.0 %
Koivisto 9.0 Ipman            :   2 (+  1,=  1,-  0), 75.0 %
Stockfish 20230125            :   8 (+  0,=  8,-  0), 50.0 %
Corchess 230125               :   2 (+  0,=  2,-  0), 50.0 %
Viridithas 7.0.0              :  14 (+ 11,=  3,-  0), 89.3 %
Protej 0.6.4                  :   6 (+  6,=  0,-  0), 100.0 %
BlackCore 5.1                 :   6 (+  3,=  3,-  0), 75.0 %
Vafra 12.3 Cfish              :  10 (+  3,=  7,-  0), 65.0 %
CorChess 20230125             :   6 (+  0,=  6,-  0), 50.0 %
Winter 2.0                    :   6 (+  5,=  1,-  0), 91.7 %
Eman 8.70                     :  20 (+  0,= 20,-  0), 50.0 %
Igel 3.4.0                    :  14 (+  8,=  6,-  0), 78.6 %
Stockfish 20230202            :   4 (+  0,=  4,-  0), 50.0 %
Polyfish 230202               :  18 (+  0,= 17,-  1), 47.2 %
Smallbrain 7.0                :   6 (+  5,=  1,-  0), 91.7 %
Charisma Light 2              :   6 (+  0,=  5,-  1), 41.7 %
Stockfish 230202              :   2 (+  0,=  2,-  0), 50.0 %
Stockfish 230125 Ivec         :   2 (+  0,=  2,-  0), 50.0 %
CorChess 20230210             :   4 (+  0,=  4,-  0), 50.0 %
Caissa 1.6                    :   2 (+  2,=  0,-  0), 100.0 %
Velvet 5.1.0                  :   4 (+  4,=  0,-  0), 100.0 %
Fat Fritz 2                   :  12 (+  2,= 10,-  0), 58.3 %
Patzer AI 020223              :   8 (+  1,=  7,-  0), 56.2 %
Berserk 11                    :   2 (+  1,=  1,-  0), 75.0 %
Clover 3.3.1                  :   2 (+  2,=  0,-  0), 100.0 %
Caissa 1.6.3                  :   4 (+  3,=  1,-  0), 87.5 %
Rebel 16.2                    :  14 (+  5,=  9,-  0), 67.9 %
Stockfish 20230218            :   6 (+  0,=  5,-  1), 41.7 %
Berserk 11.1                  :  12 (+  1,= 11,-  0), 54.2 %
Stockfish 20230224            :   2 (+  0,=  2,-  0), 50.0 %
Koivisto 9.2                  :  14 (+  6,=  8,-  0), 71.4 %
Charisma Light 1.0            :   2 (+  0,=  2,-  0), 50.0 %
Stockfish 20230128            :   4 (+  0,=  4,-  0), 50.0 %
CorChess 20230202             :   2 (+  0,=  2,-  0), 50.0 %
Charisma Blitz                :   4 (+  0,=  4,-  0), 50.0 %
Ethereal 14.00 NNUE           :  14 (+  8,=  6,-  0), 78.6 %
Stockfish 20230209            :   2 (+  0,=  1,-  1), 25.0 %
Berserk 20230130b             :   2 (+  0,=  2,-  0), 50.0 %
Charisma 250223               :  10 (+  1,=  9,-  0), 55.0 %
CorChess 20230226             :   6 (+  0,=  6,-  0), 50.0 %
Stockfish 20230227            :   2 (+  0,=  2,-  0), 50.0 %
Leptir 280223                 :   2 (+  0,=  2,-  0), 50.0 %

ShashChess 31.1 - download 
github:https://github.com/amchess/ShashChess/releases/tag/31.1



BrainLearn - UCI chess engine
Rating CEDR=3716

BrainLearn is a free, powerful UCI chess engine derived from BrainFish. It is not a complete chess program and requires a UCI-compatible GUI (e.g. XBoard with PolyGlot, Scid, Cute Chess, eboard, Arena, Sigma Chess, Shredder, Chess Partner or Fritz) in order to be used comfortably. 
Read the documentation for your GUI of choice for information about how to use Stockfish with it. 

v.23.1:
Bug fix
Stockfish patch
Depth Tweak and tuning
tunes reduction related parameters, and introduces more reduction on found good moves.
credit for this patch goes also to candirufish Yoshie2000 dubslow peregrineshahin Vizvezdenec

Individual statistics: BrainLearn 19 - 260 games (+ 56,=197,-  7), 59.4 %
Stockfish 15                  :   3 (+  0,=  3,-  0), 50.0 %
Dragon 3                      :   8 (+  0,=  8,-  0), 50.0 %
Fisherov chess monk 1.2       :  25 (+  0,= 24,-  1), 48.0 %
Revenge 3.0                   :   2 (+  1,=  1,-  0), 75.0 %
BigBallz 010922               :   8 (+  2,=  5,-  1), 56.2 %
ProteusSF Piranha 220904      :  10 (+  0,=  8,-  2), 40.0 %
Rebel 15.1a                   :   2 (+  1,=  1,-  0), 75.0 %
Nebula-vortex 1.0             :   8 (+  1,=  6,-  1), 50.0 %
Koivisto 8.16                 :   4 (+  3,=  1,-  0), 87.5 %
Dark Sister 1.9b              :   2 (+  1,=  1,-  0), 75.0 %
StockNemo 5.7.0.0             :   2 (+  2,=  0,-  0), 100.0 %
Marvin 6.1.0                  :   2 (+  1,=  1,-  0), 75.0 %
Alexandria 3.0                :   2 (+  2,=  0,-  0), 100.0 %
Berserk 10                    :   8 (+  3,=  5,-  0), 68.8 %
Caissa 1.1                    :   2 (+  2,=  0,-  0), 100.0 %
Fire NN 1072022               :   2 (+  2,=  0,-  0), 100.0 %
Frozenight 5.1.0              :   2 (+  2,=  0,-  0), 100.0 %
Lynx 0.12.0                   :   2 (+  2,=  0,-  0), 100.0 %
Trinket 3.0.0                 :   2 (+  2,=  0,-  0), 100.0 %
Stockfish 101022 Ivec         :   4 (+  0,=  4,-  0), 50.0 %
CorChess 101022               :  13 (+  1,= 11,-  1), 50.0 %
Solista Attack 2              :  15 (+  0,= 15,-  0), 50.0 %
Fatalii 0.3.1                 :   2 (+  2,=  0,-  0), 100.0 %
Francesca 0.32                :   2 (+  1,=  1,-  0), 75.0 %
Halogen 11                    :  11 (+  5,=  6,-  0), 72.7 %
Polyfish 221009               :  12 (+  0,= 12,-  0), 50.0 %
Mayhem 7.4                    :   4 (+  4,=  0,-  0), 100.0 %
RubiChess 20221001            :  12 (+  4,=  8,-  0), 66.7 %
ShashChess 25                 :  14 (+  1,= 13,-  0), 53.6 %
Eman 8.40                     :  23 (+  0,= 23,-  0), 50.0 %
Smallbrain 6.0                :   5 (+  5,=  0,-  0), 100.0 %
Stockfish 161022              :  16 (+  0,= 16,-  0), 50.0 %
AI 27.0                       :   1 (+  0,=  1,-  0), 50.0 %
RapChess 2022-10-17           :   1 (+  1,=  0,-  0), 100.0 %
BlackCore 2.0                 :   1 (+  1,=  0,-  0), 100.0 %
Viridithas 3.0.0              :   1 (+  1,=  0,-  0), 100.0 %
Vafra 12.2 Cfish              :   1 (+  0,=  1,-  0), 50.0 %
ShashChess 25.1               :   1 (+  0,=  1,-  0), 50.0 %
YuliGM PrO 4.0                :   1 (+  0,=  1,-  0), 50.0 %
Stockfish 081022              :   6 (+  1,=  4,-  1), 50.0 %
SugaR AI 131022               :   2 (+  0,=  2,-  0), 50.0 %
Dark Sister 1.9d              :   6 (+  0,=  6,-  0), 50.0 %
CorChess 171022               :   2 (+  0,=  2,-  0), 50.0 %
Fritz 18 Neuronal             :   2 (+  2,=  0,-  0), 100.0 %
pHoBiA 4.0                    :   2 (+  0,=  2,-  0), 50.0 %
Spectral Tactical 1.40        :   2 (+  0,=  2,-  0), 50.0 %
Stockfish 14.1                :   2 (+  0,=  2,-  0), 50.0 %


BrainLearn progress:
PlEngineCEDRScoreGames(%)
18Brainlearn 20.1 vulkan3730.535.505268.27
48BrainLearn 203716.4321.0049065.51
68BrainLearn 21.13711.5499.5076465.38
79BrainLearn 193709.6154.0025959.46
126BrainLearn 19.2.13701.879.0011866.95
141BrainLearn 19.13699.151.008460.71
151BrainLearn 19.23696.854.007869.23
173BrainLearn 20.23694.2280.5045861.24
184BrainLearn 183692.4209.0033662.20
195BrainLearn 0611223690.550.009652.08
222BrainLearn 173681.8150.0026456.82
242BrainLearn 213674.7101.5014868.58
287BrainLearn 9.03611.613.501875.00


BrainLearn 23.1 - download
github:https://github.com/amchess/BrainLearn/releases/tag/23


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  We provide two opening books, in two different formats: bin and ctg. This is enough to be used in almost any chess program (GUI). Of course, every book may contain errors, but this one is based on a high rating. Happy testing! Book - CTG format Customers who wish to use the CTG format book will need a GUI capable of reading this format, ie. Chessbase GUIs.  Please save the book in your book folder. We strongly recommend that you "Optimize" the book in the Book options dialog so the tournament moves are chosen. The book is very wide even in tournament mode unlike most other books. A type of book format mainly used by chess programs from Chessbase , such as Fritz, Chess Base, Komodo, FatFritz, Houdini , etc. Book - BIN format (  Used by chess GUIs Arena, Banksia and Droidfish) Binary books have some important advantages, especially for computer chess engines: space-efficient, fast on accessing and searching, more useful information.  At the most simple form, they are just a
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New version chess engine: Lc0 BT4

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LcZero - CEDR Rating=3683 vBT4: Big transformer 4. New network architecture which builds off of BT3 by adding two types of auxiliary heads, future heads and categorical value heads. The categorical value heads predict a distribution over values of q rather than a WDL outcome distribution, and the future heads predict the moves that will be played over the next two plies. The hope is that these heads will give additional information to the net to improve training speed. We've also fixed half-precision training, so this model will be larger. BT4 training started in mid-October and is expected to take a few months. It has 15 layers with 1024 embedding size, 32 heads per layer, and 1536 emb size, for roughly a doubling in size over BT3.  Individual statistics:  Lc0 0.30.0 Stockfish 16 5/13 -3 13 Games Booot 7.2 6/10 +2 10 Games Critter 1.6a 8/9 +7 9 Games Dragon 3.2 4/8 +0 8 Games Stockfish 20230729 3.5/8 -1 8 Games ShashChess 33.2 3.5/8 -1 8 Games Fisherov chess monk 1.2 3/
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Dragon NNUE by Komodo Chess - it's free!

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    Dragon by Komodo Chess Larry Kaufman: We have released Dragon at komodochess.com. Dragon uses NNUE (Neural Network Updated Efficiently) technology, originally developed for the game of shogi. Komodo has a great deal of chess knowledge in its evaluation. Training an NNUE network based on this evaluation was both an advantage and a challenge, requiring experimentation with architectures and data generation of billions of positions. The reinforcement learning phase for Dragon is in its infancy, but is already showing great promise. Dragon is a huge strength improvement over 14.1, the last release, about 197 elo in MCTS mode and 189 elo in standard mode, at CCRL blitz time control on one thread based on direct matches. With four threads, the gains were 156 elo in MCTS and 170 in standard mode. The improvement is due to the embedded neural network providing much more accurate evaluation and also in some sense gaining an extra ply or so of search by “seeing” some tactics that a normal ev
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