Category: Engine

Author(s): Cosmo Bobak (GBR), Conor Anstey (GBR), Archishmaan Peyyety (USA)
Release Date: 2025-01-27
Language(s): Rust
Repo Owner: cosmobobak
Repo URL: https://github.com/cosmobobak/viridithas

This release brings tuned search, a new net, and some generally improved internal design.

Upgrades, in chronological order:

  • Remove material corrhist. #208
  • Separate sum vector for reproducible bench. #210
  • Guard QS SEE pruning a bit more. #211
  • Remove granular depth. #212
  • Remove is_winning from movesloop. #213
  • Use mmap to share weights between multiple processes of Viridithas. #214
  • Improve NNUE inference. #216
  • Major refactor of internals. #217
  • Two SPSA tunes. #220
  • Take advantage of bucket layout to merge king planes. #221
  • Simplify continuation history indexing. #222
  • New network, ID perseverance. #223

https://github.com/cosmobobak/viridithas/releases/download/v16.0.0/viridithas-16.0.0-linux-x86-64-v1
https://github.com/cosmobobak/viridithas/releases/download/v16.0.0/viridithas-16.0.0-linux-x86-64-v2
https://github.com/cosmobobak/viridithas/releases/download/v16.0.0/viridithas-16.0.0-linux-x86-64-v3
https://github.com/cosmobobak/viridithas/releases/download/v16.0.0/viridithas-16.0.0-linux-x86-64-v4
https://github.com/cosmobobak/viridithas/releases/download/v16.0.0/viridithas-16.0.0-win-x86-64-v1.exe
https://github.com/cosmobobak/viridithas/releases/download/v16.0.0/viridithas-16.0.0-win-x86-64-v2.exe
https://github.com/cosmobobak/viridithas/releases/download/v16.0.0/viridithas-16.0.0-win-x86-64-v3.exe
https://github.com/cosmobobak/viridithas/releases/download/v16.0.0/viridithas-16.0.0-win-x86-64-v4.exe
https://github.com/cosmobobak/viridithas/archive/refs/tags/v16.0.0.zip

This is the engine that I got ChatGPT to put together for me. It’s written in C, and I have absolutely no hand in the coding of it. It’s a work-in-progress. So far compilation efforts have been in vain.

Ideally other people would turn it into something, but I’ll keep having the robot do revisions.

https://github.com/ianrastall/bear

Author(s): Andrea Manzo (ITA)
Release Date: 2025-01-17
Language(s): C++
Repo Owner: amchess
Repo URL: https://github.com/amchess/Alexander

Alexander is a free UCI chess engine derived from Stockfish family chess engines. For the evaluation function, we utilize the collaboration between Leela Chess Zero and Stockfish, for which we express our sincere gratitude. The goal is to apply Alexander Shashin theory exposed on the following book : https://www.amazon.com/Best-Play-Method-Discovering-Strongest/dp/1936277468 to improve

  • base engine strength
  • engine’s behaviour on the different positions types (requiring the corresponding algorithm) :
    • Tal
    • Capablanca
    • Petrosian
    • the mixed ones
      • Tal-Capablanca
      • Capablanca-Petrosian
      • Tal-Capablanca-Petrosian

Also during the search, to enhance it, we use both standard and Q/Self reinforcement learning.

Aligned with Stockfish
Jan 12, 2025
Increase the depth margin

More info:
Alexander Presentation

https://github.com/amchess/Alexander/releases/download/4.0/Linux.7z
https://github.com/amchess/Alexander/releases/download/4.0/Windows.7z
https://github.com/amchess/Alexander/archive/refs/tags/4.0.zip

Stockfish 17 source:
https://github.com/official-stockfish/Stockfish/archive/refs/tags/sf_17.zip

Author(s): Andrea Manzo (ITA)
Release Date: 2025-01-16
Language(s): C++
Repo Owner: amchess
Repo URL: https://github.com/amchess/ShashChess

Aligned with Stockfish patch: Jan 12, 2025 (Increase the depth margin). The AI recognized the significant added value and originality of the derivative ShashChess compared to the original Stockfish. For further details and the great novelties of this version, see this pdf document.

https://github.com/amchess/ShashChess/releases/download/38/Linux.7z
https://github.com/amchess/ShashChess/releases/download/38/Mac.7z
https://github.com/amchess/ShashChess/releases/download/38/windows.7z
https://github.com/amchess/ShashChess/archive/refs/tags/38.zip

Stockfish 17 source:
https://github.com/official-stockfish/Stockfish/archive/refs/tags/sf_17.zip

Author(s): Dan Kelsey (NLD)
Release Date: 2025-01-16
Language(s): Java
Repo Owner: kelseyde
Repo URL: https://github.com/kelseyde/calvin-chess-engine

Calvin 5.1.0 brings significant improvements in both search and evaluation. Calvin has a bigger and better neural network, with a hidden layer size of 1024 and 4 king buckets, horizontally mirrored. In search, the biggest improvement was fixing Calvin’s bugged SEE algorithm, which enabled many search and move ordering techniques. Tests against the previous release suggest a strength increase of 124 elo LTC / 106 elo STC.

To run the jar file, you will need to enable the Vector API package which Calvin uses for SIMD, via this command:

java --add-modules jdk.incubator.vector -jar path/to/calvin-chess-engine-5.1.0.jar

https://github.com/kelseyde/calvin-chess-engine/releases/download/5.1.0/calvin-chess-engine-5.1.0.jar
https://github.com/kelseyde/calvin-chess-engine/releases/download/5.1.0/calvin-wrapper-5.1.0.jar
https://github.com/kelseyde/calvin-chess-engine/archive/refs/tags/5.1.0.zip

Author(s): Marco Zerbinati (ITA)
Release Date: 2025-01-06
Language(s): C++
Repo Owner: Zerbinati
Repo URL: https://github.com/Zerbinati/JudaS-Plus

  • Enhance Experience Book functionality and add logging option
  • Fix: Enable engine to play black moves from the experience book
  • Enhancement: Configurable performance threshold and detailed logging for experience book
  • Added a new UCI option Experience Book Width to control the variety of moves selected from the experience book
  • Calibrated Default Values for Experience Book Options
  • Implemented “Experience Book Min Win Probability” filter and logging improvements
  • Added Experience Book Probing Functionality with Logging
  • Enhanced Learning Mode Option with UCI Feedback

https://github.com/Zerbinati/JudaS-Plus/releases/download/J4.0/windows.builds.7z
https://github.com/Zerbinati/JudaS-Plus/archive/refs/tags/J4.0.zip

Stockfish 17 source:
https://github.com/official-stockfish/Stockfish/archive/refs/tags/sf_17.zip

Author(s): Marco Zerbinati (ITA)
Release Date: 2025-01-08
Language(s): C++
Repo Owner: Zerbinati
Repo URL: https://github.com/Zerbinati/HypnoS-plus

HypnoS ++ is a free and strong UCI chess engine derived from Stockfish that analyzes chess positions and computes the optimal moves. HypnoS ++ does not include a graphical user interface (GUI).

https://github.com/Zerbinati/HypnoS-plus/releases/download/H1.0/windows.builds.7z
https://github.com/Zerbinati/HypnoS-plus/archive/refs/tags/H1.0.zip

Stockfish 17 source:
https://github.com/official-stockfish/Stockfish/archive/refs/tags/sf_17.zip

Author(s): Liam McGuire (USA), Eduardo Cáceres (ESP)
Release Date: 2025-01-08
Language(s): C#
Repo Owner: liamt19
Repo URL: https://github.com/liamt19/Lizard

Has a more complex network and a few search tweaks/additions. For the sake of my sanity (and because .NET can’t/doesn’t autovectorize NNUE code), this requires at least AVX2 to be performant, but will still function without it.

A Note On Bindings

This release includes C++ code from Horsie to make NNUE evaluation faster. This code is only used if your processor supports AVX2.

The Windows and Linux releases here already have it compiled and embedded as a .dll/.so within it. For technical reasons this embedded file will automatically extract itself into a file called HorsieBindings.dll/HorsieBindings.so which Lizard will try to use when it launches.

You will see “Loaded Horsie bindings!” if they are successfully loaded, or “Running without Horsie bindings” if they aren’t. The bindings aren’t required, but they do make Lizard significantly faster.

Picking A Binary

Use a …-512 binary if your processor has Avx512.
AOT binaries aren’t being included here because they are strictly slower.

https://github.com/liamt19/Lizard/releases/download/v11.2/Lizard-11_2-arm64
https://github.com/liamt19/Lizard/releases/download/v11.2/Lizard-11_2-linux
https://github.com/liamt19/Lizard/releases/download/v11.2/Lizard-11_2-linux_512
https://github.com/liamt19/Lizard/releases/download/v11.2/Lizard-11_2-win-512.exe
https://github.com/liamt19/Lizard/releases/download/v11.2/Lizard-11_2-win.exe
https://github.com/liamt19/Lizard/archive/refs/tags/v11.2.zip

 

Author(s): Marco Zerbinati (ITA)
Release Date: 2025-01-06
Language(s): C++
Repo Owner: Zerbinati
Repo URL: https://github.com/Zerbinati/JudaS-Plus

JudaS ++ is a free and strong UCI chess engine derived from Stockfish that analyzes chess positions and computes the optimal moves. JudaS ++ does not include a graphical user interface (GUI).

https://github.com/Zerbinati/JudaS-Plus/releases/download/J2.0/windows.builds.7z
https://github.com/Zerbinati/JudaS-Plus/archive/refs/tags/J2.0.zip

Stockfish 17 source:
https://github.com/official-stockfish/Stockfish/archive/refs/tags/sf_17.zip

Author(s): Thorsten Greiner (GER)
Release Date: 2025-01-07
Language(s): C++
Repo Owner: thgreiner
Repo URL: https://github.com/thgreiner/amy

What’s Changed

Full Changelog: v0.9.5…v0.9.6

https://github.com/thgreiner/amy/releases/download/v0.9.6/amy-0.9.6.tar.gz
https://github.com/thgreiner/amy/archive/refs/tags/v0.9.6.zip

Eubos chess is a multi-threaded Java chess engine. Eubos uses a standard alpha-beta negascout algorithm with transposition hashing and quiescence search extension. It uses lazy move generation and lazy evaluation.

The evaluation function takes account of the following factors

  • material balance
  • piece mobility
  • pawn structure
  • king safety
  • tactical threats

It knows about draws by 3-fold repetition and insufficient material.

https://github.com/cjbolt/EubosChess/releases/download/v3.8/Eubos.bat
https://github.com/cjbolt/EubosChess/releases/download/v3.8/Eubos.jar
https://github.com/cjbolt/EubosChess/archive/refs/tags/v3.8.zip

Author(s): Colin Jenkins (GBR)
Release Date: 2025-01-06
Language(s): JavaScript
Repo Owner: op12no2
Repo URL: https://github.com/op12no2/lozza

Lozza was primarily created for use in browsers, but can also be used with traditional chess UIs via Node.js and on pretty-much any platform (see below). Note however that Lozza is relatively slow compared to compiled engines of a similar design, which also makes her relatively weak.

This is a Lozza 4 re-release.

The original Lozza 4 release caused problems for some users. For those that ran it successfully, results (e.g. CCRL Blitz) can stand because no peformative changes have been made. However, please replace with this re-release anyway; thanks.

Please use a recent version of Node if possible (they are always improving performance). The latest stable version is 22.

https://nodejs.org

Changes

Train generation 3 net.
Use ADJACENT, not DIST.
Simplify QS and don’t go into QS if in check.
Scale eval by 1.9. Scale UCI cp by 1.9.
Add perspective (currently unused).
Use the Mersene Twister from cwtch for randoms.
Move futility alpha test to move loop.
Use hash move in QS.
Optmise deferral of accumulator update a bit more.
Fix some web stuff. Add improving indicator (failed to get it to gain so far).
Prune QS with quickSee(). Only count nodes that iterate moves.
Put eval in TT before search.
Optimise castling a bit.
Simplify search recursion.
Allow successive NMP and beta pruning.
Bigger net 768x128x1 srelu.
Make sure all UE updates (e.g. castling) are a single accumulator loops.
Defer UE to after legal check (doh!) and don’t check pre-determined legal moves.
Minor tweaks for datagen + net command.

https://github.com/op12no2/lozza/releases/download/4/lozza4.zip
https://github.com/op12no2/lozza/archive/refs/tags/4.zip

Author(s): Peter Österlund
Release Date: 2025-01-05
Language(s): C++
Repo Owner: peterosterlund2
Repo URL: https://github.com/peterosterlund2/texel

Neural network improvements:

  • Speed up matrix multiplication for AVX-512.
  • New network based on new training data.
  • Use 4 “heads” (all NN layers except the first) for evaluation. The active head depends on the number of pieces on the board.
  • Increase NN layer 1 output size from 256 to 384.

Tablebases:

  • Measure thinking time more accurately. Useful when TB files are on mechanical disks.
  • Better handling of DTZ scores in search.
  • Avoid expensive (wrong side to move) DTZ probes in search.
  • Add UCI parameter to control required search depth for DTZ probes.
  • Measure time required to perform a TB probe instead of guessing. This avoids time losses in fast games when TB files are on mechanical disks.
  • Allow RTB WDL probes in some cases even if hmc > 0.
  • Change TB swindle depth from 16 to “15+minProbeDepth”, to avoid slowdown in late middlegame/early endgame when TB files are on mechanical disks.

Search:

  • Implement the counter move heuristic.
  • Implement multi-cut pruning based on singular search score.
  • Adjust singular extension search parameters.
  • Allow both extension and reduction in the same search node.
  • Remove no longer useful “recapture” and “going into pawn endgame” extensions.
  • Reduce aspiration window size.

Other:

  • Use multiple threads to initialize the transposition table.
  • Better handling of mate scores in the transposition table.
  • Fix handling of empty strings in UCI string options.

https://github.com/peterosterlund2/texel/releases/download/1.12/texel112.7z
https://github.com/peterosterlund2/texel/archive/refs/tags/1.12.zip