Weights tuning for SoFCheck

This repository contains notebooks and datasets to tune the evaulation weights in SoFCheck chess engine.

The engine uses the tuning method described in this post (in Russian). It is similar to Texel's tuning method.

Datasets

Datasets are prepared in canonical SoFGameSet format, as generated by BattleField. To extract CSV with coefficients from these datasets, you need to build SoFCheck and use the make_datasets utility from it. All the data is bzip2-compressed to take less disk space.

The datasets are as follows:

• stockfish_20k.sgs.xz contains 20'000 games played by Stockfish 13 against itself on short time control (~100ms).
• sofcheck1_30k.sgs.xz contains 30'000 games played between SoFCheck commit 1c75e30 (call it v1) and SoFCheck commmit 0a52f13 (call it v2). 10'000 games were played v1 against v1, 10'000 games were played v1 against v2 and 10'000 games were played v2 against v2.
• sofcheck2_100k.sgs.xz contains 100'000 games between SoFChecks from commits faebcce, d4ded36, f8ce5cc and 6bc597b. There are ten unordered pairs possible between these engines (including games with itself), and each pair played 10'000 games against each other.
• sofcheck3_40k.sgs.xz contains 40'000 games between SoFChecks from commits e498bab and a7df920. Each of the engines played 10'000 games with itself and 20'000 games with the other engine.

More datasets may be available later.

Notebooks

Jupyter notebooks, which we used to train SoFCheck, are also lacated in this repository. Note that the results may be not completely reproducible because of randomness.