# DeepLearningShogi

> shogi engine

**Wikidata**: [Q104606212](https://www.wikidata.org/wiki/Q104606212)  
**Source**: https://4ort.xyz/entity/deeplearningshogi

## Summary  
DeepLearningShogi (dlshogi) is a free and open-source shogi engine designed for playing the Japanese game of shogi using deep learning techniques. It runs on both Microsoft Windows and Unix-like operating systems and is distributed under the GNU General Public License version 3.0.

## Key Facts  
- Sport: Shogi  
- Aliases: dlshogi  
- License: GNU General Public License, version 3.0  
- Latest stable release: v0.1.1 (published November 22, 2021)  
- First release: v0.1.0 (published October 2, 2021)  
- Operating systems supported: Microsoft Windows, Unix-like systems  
- Programming language: C++ (Q2407)  
- Instance of: Free software  
- Copyright status: Copyrighted  
- Source code repository: https://github.com/TadaoYamaoka/DeepLearningShogi  

## FAQs  
### Q: What is DeepLearningShogi used for?  
A: DeepLearningShogi is a shogi engine used to play and analyze games of shogi using artificial intelligence powered by deep learning models. It can be used by players, developers, or researchers interested in computer shogi.

### Q: Is DeepLearningShogi free to use and modify?  
A: Yes, DeepLearningShogi is free software released under the GNU General Public License version 3.0, which allows users to run, study, modify, and redistribute the software.

### Q: On which platforms does DeepLearningShogi run?  
A: DeepLearningShogi supports both Microsoft Windows and Unix-like operating systems such as Linux.

## Why It Matters  
DeepLearningShogi represents a significant advancement in the domain of computer shogi by applying modern deep learning methods to gameplay and analysis. As a free and open-source project, it lowers the barrier for enthusiasts and researchers who wish to explore AI-driven shogi engines without relying on proprietary solutions. Its availability encourages community contributions, promotes transparency in algorithmic development, and supports educational initiatives in machine learning and game theory. By making advanced shogi AI accessible, DeepLearningShogi contributes to the broader ecosystem of open science and recreational computing.

## Notable For  
- Being one of the early open-source shogi engines leveraging deep learning  
- Supporting cross-platform usage with compatibility for both Windows and Unix-like systems  
- Releasing under a strong copyleft license (GPLv3), ensuring derivative works remain open  
- Providing a modular codebase hosted publicly on GitHub for collaborative development  

## Body  
### Overview  
DeepLearningShogi is a shogi-playing engine that uses neural networks to evaluate positions and make decisions during gameplay. Developed by Tadao Yamaoka, it was made publicly available through GitHub and licensed under the GNU GPL v3.0.

### Development and Licensing  
The software's source code is hosted at [https://github.com/TadaoYamaoka/DeepLearningShogi](https://github.com/TadaoYamaoka/DeepLearningShogi). The licensing information confirms its classification as free software, allowing unrestricted access to the source and permitting modification and redistribution under the same license terms.

### Releases  
Two notable releases have been documented:
- **Version 0.1.0** – Released on October 2, 2021 ([GitHub tag](https://github.com/TadaoYamaoka/DeepLearningShogi/releases/tag/v0.1.0))  
- **Version 0.1.1** – Released on November 22, 2021 ([GitHub tag](https://github.com/TadaoYamaoka/DeepLearningShogi/releases/tag/v0.1.1)), marked as the preferred/latest version  

### Technical Details  
- **Programming Language**: Written primarily in C++  
- **Operating Systems Supported**: Microsoft Windows and Unix-like systems  
- **Sport Application**: Specifically built for shogi, a traditional Japanese strategy board game  

### Community and Accessibility  
As an open-source initiative, DeepLearningShogi benefits from public scrutiny and potential community contributions. Hosting on GitHub enables easy discovery, issue tracking, and collaboration among developers and shogi researchers.

## References

1. [Source](https://github.com/TadaoYamaoka/DeepLearningShogi#%E3%83%A9%E3%82%A4%E3%82%BB%E3%83%B3%E3%82%B9)
2. [Source](https://github.com/TadaoYamaoka/DeepLearningShogi/blob/master/cppshogi/LICENSE)
3. [Source](https://api.github.com/repos/TadaoYamaoka/DeepLearningShogi)
4. [Release 0.1.0. 2021](https://github.com/TadaoYamaoka/DeepLearningShogi/releases/tag/v0.1.0)
5. [Release 0.1.1. 2021](https://github.com/TadaoYamaoka/DeepLearningShogi/releases/tag/v0.1.1)