Since you’re here...

We hope you will consider supporting us today. We need your support to continue to exist, because good entries are more and more work time. Every reader contribution, however big or small, is so valuable. Support "Chess Engines Diary" even a small amount– and it only takes a minute. Thank you.
============================== My email: jotes@go2.pl



Chess engine: Lambergar 1.1

-

 


Lambergar - UCI chess engine  Rating Chess Engines Diary CEDR=3061
Lambergar is a chess engine developed in the Zig programming language. 

The name "Lambergar" is a nod to the Slovenian folk romance, Pegam and Lambergar, which recounts the epic struggle between Jan Vitovec and Krištof Lambergar (Lamberg). This narrative of fortitude and rivalry provided a fitting namesake for this chess engine.

Lambergar is licensed under the MIT License. Check out LICENSE.txt for the full text. Feel free to use this program, but please credit this repository in your project if you use it.

v.1.1:
Builds
Currently, there are five builds:

x86-64-v3: AVX2 support, best for using with NN evaluation and should be a preferred choice for best performance.
x86-64-v2: popcount support, suitable for modern computers.
x86-64-v1: vintage version is for really old computers.
aarch64-linux: version for Raspberry Pi 5,
x86-64-v4: AVX-512 support.
Release Notes
Changed some conditions for quiet move pruning based on history.
Updated the equation for calculating the bonus for history.
Implemented SIMD for the most computationally demanding functions in NNUE calculation, increasing NPS by 45%.
Improved the speed of the move generator, increasing NPS by an additional 15%.
Overall, this results in a 60% increase in NPS. At implemented time controls, this translates to 50% more nodes searched per move and 10% more depth per move.
New net called trstenjak.nnue, same architecture as before, but stronger. Trained on 800M positions of self play.
Compatible with zig version 0.14.0.
Time controls 10s+0.1s

Score of Lambergar-1.1 vs Lambergar_1.0: 631 - 94 - 500  [0.719] 1225
...      Lambergar-1.1 playing White: 388 - 32 - 193  [0.790] 613
...      Lambergar-1.1 playing Black: 243 - 62 - 307  [0.648] 612
...      White vs Black: 450 - 275 - 500  [0.571] 1225
Elo difference: 163.4 +/- 15.2, LOS: 100.0 %, DrawRatio: 40.8 %

Lambergar 1.0 vs other engines:
Alexander 4.01.5/6-36 Games
JudaS ++ 5.01/6-46 Games
ShashChess 380.5/6-56 Games
DarkSeid 5.20.5/6-56 Games
Artemis 6TR0/6-66 Games
Aurora 202410074/4+44 Games
Fortuna 1.0 JA4/4+44 Games
Tcheran 5.14/4+44 Games
Zangdar 3.042/4+04 Games
Troubadour 1.10/4-44 Games
Troubadour 1.30/4-44 Games
Knightx 4.22/2+22 Games
Amy 0.9.6-pre AB JA2/2+22 Games
Dog 3.02/2+22 Games
Vault 0.4.1 JA2/2+22 Games
Ssehc 1.02/2+22 Games
GOOB 1.8.92/2+22 Games
CeeChess 1.42/2+22 Games
LizardBrain2/2+22 Games
Andoma 0.1.1 JA2/2+22 Games
Queen 4.052/2+22 Games



github:https://github.com/jabolcni/Lambergar/releases/

Sample game of this engine:




Partia mi si� podoba�a (ChessBase 16)

ChessBase

Lambergar 0.6.0–Knightx 4.11–0B302024.07.18.NewEnginesTest1.63Chess Engines Diary20.07.2024
[%evp 0,90,19,38,40,41,51,32,66,38,46,19,6,27,34,13,17,12,19,8,15,18,22,-7,13,-3,3,28,72,-21,49,81,92,62,79,84,76,76,75,69,109,129,119,100,113,124,101,122,106,91,127,106,114,120,129,129,110,110,124,159,170,196,194,196,200,196,224,224,245,253,253,253,258,253,250,259,269,277,271,295,310,325,323,333,336,352,355,374,413,419,425,435,446] 1.e4 c5 2.f3 c6 3.b5 e6 4.0-0 ge7 5.c3 d5 6.exd5 xd5 7.e1 a6 8.a4 b5 9.c2 b7 10.d4 d8 11.e4 h5 12.bd2 cxd4 13.cxd4 h6 14.h3 g6 15.f1 h4 16.e3 a5 17.xh4 xh4 18.xb7 xb7 19.f3 d7 20.c6 e7 21.xa6 0-0 22.xb5 fd8 23.g3 d6 24.c6 e8 25.e4 d6 26.xh4 xh4 27.a4 b7 28.a5 xb2 29.a6 a8 30.d5 exd5 31.a7 xg3 32.fxg3 b5 33.ab1 xb1 34.xb1 xa7 35.a1 f6 36.xa7 f7 37.d4 xa1+ 38.xa1 g6 39.f2 f5 40.e3 h5 41.d4 e6 42.c3 d6 43.b4+ e6 44.c5 g6 45.a3 g5 46.b4 h4 1–0
Download PGN

Comments

Post a Comment

Popular posts from this blog

New Strong Engines Test, by Chess Engines Diary, 2024.04.12

-
Image
  💾  552 (!) games from the tournament download   👍 @chessenginesdiary  Country - Poland, City -  Malbork 🕓 Time 3'+3" 💻HP Pavilion i5-1035G1 8GB RAM 🖬 GUI-Banksia All  CEDR  317.321 games download  (01.04.2024 - 3'+3")  HypnoS 030424, Yuli GM Pro 16, Stockfish 16.1 and ShashChess 35 . These four engines scored the same number of points and placed at the top of the table in this strong tournament. Tech table: Engine KN/move NPS dep/mov time/mov mov/game time/game fails Alexandria 6.1.0 3218 576429 30.2 5.6 56.7 316.2 Berserk 13 4779 841025 36.7 5.7 56.0 318.1 Brainlearn 28 2275 366977 31.4 6.2 43.5 269.4 Caissa 1.18 5492 923486 30.2 5.9 50.4 299.7 Clover 6.1.19 4803 854377 31.4 5.6 62.2 349.4 Cool Iris 12.10 2201 356730 27.6 6.2 51.2 315.5 CorChess 20240331 2253 372774 27.4 6.0 52.2 315.8 Crystal 8 3582 571994 20.3 6.3 47.7 298.8 Fire 9.3 5225 876565 22.0 6.0 55.5 331.1 Fisherov chess monk 1.2 34...
Read more

New chess opening book: M11.2 (bin and ctg)

-
Image
  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 ar...
Read more

Dragon NNUE by Komodo Chess - it's free!

-
Image
    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 ...
Read more

Chess engines: ChessKiss 1.8

-
Image
ChessKiss - UCI engines,  Thanks to the Author: Abel Belzunces v.1.8 -Lazy eval improved -Fixed some issues in pawn evaluation -New now pawn penalty when ending -Some performance gains... -New recapture extension -Pawn cache improved -Evaluation performance improved a bit -New book -Seems book moves were not very random -Some bugs fixed here and there -Now rook and knight pairs are also evaluated -Now root nodes are evaluated differently -Time for move is calculated differently Chesskiss 1.8 download
Read more

New version chess engine: Lc0 BT4

-
Image
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...
Read more

Houdidit 6.03

-
Image
Michael Byrne: It has been alleged that the chess engine Houdini 6.03 was based on part, the open source chess engine Stockfish. If true, this will allows anyone who purchased the engine access to the source under Stockfish's GPL license. I purchased the engine multiple times over the years and I am now pleased to make the source available to everyone, as it is my opinion that the allegations are true and the evidence provided is overwhelming. In addition, you will find some custom compiled versions of the engine available to all ( allowed under Stockfish's GPL license). The engine here has been renamed to Houdidit , as in guess "Who did it?" and to keep it different from the engine Mr. Houdart was selling which in my opinion was in violation of Stockfish's GPL , i.e, selling Houdini without disclosing it was based, in part, on the open source Stockfish, nor releasing its source. A full discussion of this issue may be found here: http://talkchess.com/foru...
Read more