Stockfish README

The project's README from github.com/official-stockfish/Stockfish. As one markdown file: README.md.

Stockfish

Stockfish

A free and strong UCI chess engine.
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Website Fishtest Discord

Overview

Stockfish is a free and strong UCI chess engine derived from Glaurung 2.1 that analyzes chess positions and computes the optimal moves.

Stockfish does not include a graphical user interface (GUI) that is required to display a chessboard and to make it easy to input moves. These GUIs are developed independently from Stockfish and are available online. Read the documentation for your GUI of choice for information about how to use Stockfish with it.

See also the Stockfish documentation for further usage help.

Files

This distribution of Stockfish consists of the following files:

Contributing

See Contributing Guide.

Donating hardware

Improving Stockfish requires a massive amount of testing. You can donate your hardware resources by installing the Fishtest Worker and viewing the current tests on Fishtest.

Improving the code

In the chessprogramming wiki, many techniques used in Stockfish are explained with a lot of background information. The section on Stockfish describes many features and techniques used by Stockfish. However, it is generic rather than focused on Stockfish's precise implementation.

The engine testing is done on Fishtest. If you want to help improve Stockfish, please read this guideline first, where the basics of Stockfish development are explained.

Discussions about Stockfish take place these days mainly in the Stockfish Discord server. This is also the best place to ask questions about the codebase and how to improve it.

Compiling Stockfish

Stockfish has support for 32 or 64-bit CPUs, certain hardware instructions, big-endian machines such as Power PC, and other platforms.

On Unix-like systems, it should be easy to compile Stockfish directly from the source code with the included Makefile in the folder src. In general, it is recommended to run make help to see a list of make targets with corresponding descriptions. An example suitable for most Intel and AMD chips:

cd src
make -j profile-build

Detailed compilation instructions for all platforms can be found in our documentation. Our wiki also has information about the UCI commands supported by Stockfish.

Terms of use

Stockfish is free and distributed under the GNU General Public License version 3 (GPL v3). Essentially, this means you are free to do almost exactly what you want with the program, including distributing it among your friends, making it available for download from your website, selling it (either by itself or as part of some bigger software package), or using it as the starting point for a software project of your own.

The only real limitation is that whenever you distribute Stockfish in some way, you MUST always include the license and the full source code (or a pointer to where the source code can be found) to generate the exact binary you are distributing. If you make any changes to the source code, these changes must also be made available under GPL v3.

Acknowledgements

Stockfish uses neural networks trained on data provided by the Leela Chess Zero project, which is made available under the Open Database License (ODbL).

Stockfish (official-stockfish/Stockfish)

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这是什么?Stockfish 是一个免费且强大的 UCI 国际象棋引擎,源自 Glaurung 2.1,它可以分析国际象棋局面并计算出最佳走法。
那它是一个带棋盘、我可以直接在上面下棋的程序吗?不是——它只是引擎,没有图形界面。你需要搭配一个独立开发的国际象棋图形界面来显示棋盘并输入走法,Stockfish 则在底层进行分析。
我怎么把它跑起来?从源代码编译:在类 Unix 系统上使用 src 文件夹里自带的 Makefile,先用 'make help' 列出编译目标(其中有一个示例目标适合大多数 Intel 和 AMD 芯片)。所有平台的详细说明都在 wiki 里。
它能在什么样的硬件上运行?它可以在 32 位或 64 位 CPU 上运行,在硬件支持时会利用某些硬件指令,还支持 Power PC 等大端序机器等多种平台。
我能把它用在自己的应用里,甚至拿去卖吗?可以——GPL v3 允许你重新分发它、出售它,或者基于它开发项目。但有个条件:任何分发都必须附带许可证和完整源代码,而且你的修改也必须以 GPL v3 发布。
Stockfish 用了神经网络吗?用了——它使用 NNUE 来评估局面。发行包中包含一个 .nnue 扩展名的文件,用来存储神经网络,二进制发行版里也内置了这个文件。
它神经网络的训练数据是从哪来的?来自 Leela Chess Zero 项目提供的数据,该项目以开放数据库许可证(ODbL)发布这些数据。
我能怎么帮 Stockfish 变得更强?改进它需要大量的测试:你可以安装 Fishtest Worker,把硬件捐给测试框架,或者按照开发指南来改进代码。讨论主要在 Stockfish Discord 上进行。
What are similar projects?dlib, ninja, tensorflow, AirSim, CNTK, DeepSpeech, caffe, openage
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