Since you’re here...

... we have a small favour to ask. More people, like you, are reading and supporting our blog: "Chess Engines Diary". And unlike many other sites and blogs, we made the choice to keep our articles open for all, regardless of where they live or what they can afford to pay.

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: Rofchade 3.0 NNUE (Mac, Linux, Rapberry Pi and Windows)



Rofchade is a UCI chess engine written in C++.
Author- Ronald Friederich.  Rating CEDR=3118

RofChade an UCI compliant chess engine by Ronald Friederich, written in C++. While its over the board tournament debut already occured at the PT 53 in Spring 2018, RofChade was first released in August 2018. However, the program's name was already established after the author made first attempts in chess programming in the 90s, combining his initials and rochade, the Dutch term for castling. Despite initially using a tapered eval of middlegame and endgame material and asymmetrical piece-square tables only, albeit Texel tuned and along with a sophisticated parallel search, RofChade 1.0 nevertheless already played in the 2700+ Elo range. RofChade 2.0 in December 2018, came with an improved evaluation considering pawn structure and king safety.

From the author:
I’ve been doing a lot of NN training for TCEC season 22, which eventually resulted in an unbelievable 4th place in the premier division! The infra final for 3th place against Lc0 showed that there is still a mayor gap between the top 3 engines and the rest including rofChade, but still an amazing result.
After the tournament I didn’t have much time to work on rofChade anymore, so it took some time to release the first NN version of rofChade, but here it is!
The current NN network architecture is HALFKA (2×256)x32x32x1. For now, this still gives the best results for rofChade. The network is trained with 2.8B by rofChade generated positions. Around 600M of them are FRC positions. The positions have been rescored a few times with intermediate networks to simulate Reinforcement learning.
The NN code is implemented from scratch, the matrix calculations are heavily influenced by the Cfish implementation. For the training of the networks an older version of the nnue-pytorch trainer from Stockfish is used as base.
To be able to generate FRC positions for training, rofChade 3.0 also supports FRC and DFRC chess variants.
I also upgraded the version of the fathom library, so that 7-men syzygy tablebases are also supported (although I haven’t been able to test if it works).

A special thanks to this version goes to the following persons/groups:
Ronald de Man for his matrix calculations in Cfish and the syzygy tablebase library
The group that develops the nnue-pytorch trainer (and their interesting discussions on discord)
Andrew Grant for sharing his experience with his FRC implementation and perft test data. It helped me to discover some unexpected FRC bugs
Jon Dart for the fathom library and updates on it
Frank Quisinsky for letting intermediate rofChade versions play in it’s tournament
IpmanChess for testing some intermediate rofChade versions
Graham banks and the rest of the CCRL team for doing a great testing job for so long
The TCEC and CCC team to organize great tournaments
Everybody else who enjoys (computer) chess!

Individual statistics: RofChade 2.3 - 120 games (+ 18,= 73,- 29), 45.4 %
Ethereal 12.75 NNUE           :   2 (+  0,=  0,-  2),  0.0 %
Fritz 17                      :   8 (+  1,=  4,-  3), 37.5 %
Arasan 23.0                   :   2 (+  1,=  1,-  0), 75.0 %
Koivisto 6.0                  :   2 (+  0,=  2,-  0), 50.0 %
Gogobello 3.0                 :   4 (+  0,=  3,-  1), 37.5 %
Xiphos 0.6.1                  :   8 (+  0,=  7,-  1), 43.8 %
Wasp 4.50                     :   2 (+  1,=  1,-  0), 75.0 %
Tornado Dec 9 2020            :   6 (+  1,=  5,-  0), 58.3 %
Clover 2.4                    :   4 (+  0,=  4,-  0), 50.0 %
Laser 1.7                     :   8 (+  0,=  6,-  2), 37.5 %
Minic 3.13                    :   2 (+  0,=  2,-  0), 50.0 %
Booot 6.5                     :   8 (+  1,=  6,-  1), 50.0 %
Schooner 2.2                  :   4 (+  0,=  4,-  0), 50.0 %
Dark Toga 1.1                 :   2 (+  1,=  0,-  1), 50.0 %
Defenchess 2.3                :   8 (+  0,=  7,-  1), 43.8 %
Roc 2020Aug05                 :   8 (+  2,=  3,-  3), 43.8 %
Andscacs 0.95092              :   6 (+  1,=  4,-  1), 50.0 %
DanaSah 9.0                   :   2 (+  1,=  0,-  1), 50.0 %
Weiss 2.0                     :   6 (+  4,=  0,-  2), 66.7 %
Seer 2.2.0                    :   2 (+  0,=  2,-  0), 50.0 %
Minic 3.17                    :   2 (+  1,=  0,-  1), 50.0 %
Berserk 7                     :   2 (+  0,=  2,-  0), 50.0 %
Nemorino 6.00                 :   2 (+  0,=  1,-  1), 25.0 %
Arasan 23.2                   :   2 (+  0,=  1,-  1), 25.0 %
Seer 2.4.0                    :   2 (+  0,=  1,-  1), 25.0 %
Wasp 5.20 second compiles     :   2 (+  1,=  1,-  0), 75.0 %
Minic 3.18                    :   2 (+  0,=  1,-  1), 25.0 %
Clover 3.0                    :   2 (+  1,=  0,-  1), 50.0 %
Toga IV                       :   2 (+  0,=  2,-  0), 50.0 %
RubiChess 20220223            :   2 (+  0,=  0,-  2),  0.0 %
Arasan 23.3                   :   2 (+  0,=  1,-  1), 25.0 %
Wasp 5.50                     :   2 (+  1,=  0,-  1), 50.0 %
Clover 3.1                    :   2 (+  0,=  2,-  0), 50.0 %


Rofchade 3.0 download


Comments

Popular Posts