RLMatrix 0.5.1

.NET 8.0 This package targets .NET 8.0. The package is compatible with this framework or higher. .NET Standard 2.0 This package targets .NET Standard 2.0. The package is compatible with this framework or higher. 
dotnet add package RLMatrix --version 0.5.1
                    


                    

                
NuGet\Install-Package RLMatrix -Version 0.5.1
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package. 
<PackageReference Include="RLMatrix" Version="0.5.1" />
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
<PackageVersion Include="RLMatrix" Version="0.5.1" />
                    


                            Directory.Packages.props
                        

                    

                
<PackageReference Include="RLMatrix" />
                    


                            Project file
For projects that support Central Package Management (CPM), copy this XML node into the solution Directory.Packages.props file to version the package. 
paket add RLMatrix --version 0.5.1
                    


                    

                
#r "nuget: RLMatrix, 0.5.1"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package. 
#addin nuget:?package=RLMatrix&version=0.5.1
                    


                            Install as a Cake Addin
                        

                    

                
#tool nuget:?package=RLMatrix&version=0.5.1
                    


                            Install as a Cake Tool

RLMatrixBanner

🚀 RLMatrix - Advanced Reinforcement Learning in C#

RLMatrix provides a comprehensive reinforcement learning framework for C# developers with performance exceeding Python alternatives. Built with TorchSharp, RLMatrix offers a type-safe, high-performance environment for developing and deploying reinforcement learning solutions.

NuGet TorchSharp Discord

💬 Get in Touch

  • Discord: Join our community server for discussions, support, and updates
  • GitHub Issues: Report bugs or request features through our GitHub issues
  • Email: For business inquiries, contact adrian@sieradzki.io

🏁 Getting Started

Please visit our official documentation for the most up-to-date getting started guides and tutorials.

⚠️ Note: The examples in this repository are being updated. For more current examples, check out our testing repository.

✨ Key Features

  • Comprehensive Algorithm Library: Includes PPO, DQN with all popular modifications (up to C51 and DQN Rainbow), GAIL, and more algorithms on the way
  • Revolutionary DRL Workflow: Thanks to C# source generation in the toolkit, you can focus on your domain problem rather than wrestling with complex API requirements
  • Multi-Head Support: Handle continuous, discrete, and mixed action spaces simultaneously in a single agent
  • RNN Integration: Enable recurrent neural networks with a simple option toggle for sequential or partial observability problems
  • Pure C# Implementation: Built entirely in C# with TorchSharp backend, providing native performance and complete type safety
  • Game Engine Ready: Battle-tested in Unity and Godot
  • Superior Performance: Faster and more stable than Python's stable-baselines, ml-agents, and Godot RL agents
  • Multi-Environment Training: Scale learning across parallel (optionally networked) environments
  • Real-time Monitoring: Built-in dashboard for visualizing training metrics
  • Industrial-Grade Distributed Training: High-performance, fault-tolerant networked architecture ready for large-scale reinforcement learning deployments
  • Transparent Source Code: Clean, well-documented codebase that's easy to extend or customize

Training Example

🗺️ Roadmap

  • Improve documentation and examples
  • Expand algorithm library with additional state-of-the-art methods
  • Further enhance Godot and Unity integration
  • Add more tools for imitation learning and GAIL
  • Test and optimize support for non-Windows non-CUDA platforms
  • Streamline inference and deployment workflows

📄 License

RLMatrix is licensed under the RLMatrix Comprehensive Dual License Agreement

🚀 RLMatrix - C#中的高级强化学习

RLMatrix为C#开发者提供了一个全面的强化学习框架，其性能超越了Python替代方案。使用TorchSharp构建，RLMatrix提供了一个类型安全、高性能的环境，用于开发和部署强化学习解决方案。 NuGet TorchSharp Discord

💬 联系我们

  • Discord: 加入我们的社区服务器进行讨论、获取支持和更新
  • GitHub Issues: 通过GitHub issues报告错误或请求新功能
  • 电子邮件: 商务咨询，请联系 adrian@sieradzki.io

🏁 开始使用

请访问我们的官方文档获取最新的入门指南和教程。

⚠️ 注意: 此代码库中的示例正在更新中。要获取更多当前示例，请查看我们的测试代码库。

✨ 主要特点

  • 全面的算法库: 包括PPO、DQN及其所有流行的修改版本（最高可达C51和DQN Rainbow）、GAIL，以及更多即将推出的算法
  • 革命性的DRL工作流: 得益于工具包中的C#源代码生成功能，您可以专注于领域问题，而不必纠结于复杂的API要求
  • 多头支持: 在单个智能体中同时处理连续、离散和混合动作空间
  • RNN集成: 通过简单的选项开关启用递归神经网络，以处理顺序或部分可观察性问题
  • 纯C#实现: 完全使用C#构建，搭配TorchSharp后端，提供原生性能和完整的类型安全性
  • 游戏引擎就绪: 在Unity和Godot中经过实战测试
  • 卓越性能: 比Python的stable-baselines、ml-agents和Godot RL agents更快速和稳定
  • 多环境训练: 通过并行（可选网络化）环境扩展学习
  • 实时监控: 内置仪表板用于可视化训练指标
  • 工业级分布式训练: 高性能、容错网络架构，为大规模强化学习部署做好准备
  • 透明源代码: 干净、文档齐全的代码库，易于扩展或自定义 训练示例

🗺️ 路线图

  • 改进文档和示例
  • 扩展算法库，增加更多最先进的方法
  • 进一步增强Godot和Unity集成
  • 添加更多用于模仿学习和GAIL的工具
  • 测试和优化对非Windows非CUDA平台的支持
  • 简化推理和部署工作流

📄 许可证

RLMatrix采用RLMatrix综合双重许可协议

Product Compatible and additional computed target framework versions.
.NET net5.0 was computed.  net5.0-windows was computed.  net6.0 was computed.  net6.0-android was computed.  net6.0-ios was computed.  net6.0-maccatalyst was computed.  net6.0-macos was computed.  net6.0-tvos was computed.  net6.0-windows was computed.  net7.0 was computed.  net7.0-android was computed.  net7.0-ios was computed.  net7.0-maccatalyst was computed.  net7.0-macos was computed.  net7.0-tvos was computed.  net7.0-windows was computed.  net8.0 is compatible.  net8.0-android was computed.  net8.0-browser was computed.  net8.0-ios was computed.  net8.0-maccatalyst was computed.  net8.0-macos was computed.  net8.0-tvos was computed.  net8.0-windows was computed.  net9.0 is compatible.  net9.0-android was computed.  net9.0-browser was computed.  net9.0-ios was computed.  net9.0-maccatalyst was computed.  net9.0-macos was computed.  net9.0-tvos was computed.  net9.0-windows was computed.  net10.0 was computed.  net10.0-android was computed.  net10.0-browser was computed.  net10.0-ios was computed.  net10.0-maccatalyst was computed.  net10.0-macos was computed.  net10.0-tvos was computed.  net10.0-windows was computed. 
.NET Core netcoreapp2.0 was computed.  netcoreapp2.1 was computed.  netcoreapp2.2 was computed.  netcoreapp3.0 was computed.  netcoreapp3.1 was computed. 
.NET Standard netstandard2.0 is compatible.  netstandard2.1 was computed. 
.NET Framework net461 was computed.  net462 was computed.  net463 was computed.  net47 was computed.  net471 was computed.  net472 was computed.  net48 was computed.  net481 was computed. 
MonoAndroid monoandroid was computed. 
MonoMac monomac was computed. 
MonoTouch monotouch was computed. 
Tizen tizen40 was computed.  tizen60 was computed. 
Xamarin.iOS xamarinios was computed. 
Xamarin.Mac xamarinmac was computed. 
Xamarin.TVOS xamarintvos was computed. 
Xamarin.WatchOS xamarinwatchos was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages (3)

Showing the top 3 NuGet packages that depend on RLMatrix:

Package Downloads
RLMatrix.Godot

Deep Reinfocement Learning Library wiring RLMatrix with Godot objects for easy of use with Godot Engine
RLMatrix.WinformsChart

Quick Winforms Chart for RL Matrix
RLMatrix.Server

Server components for Deep Reinforcement Learning in .NET

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last Updated
0.5.1 54 6/27/2025
0.4.3.8 637 2/12/2025
0.4.3.3 1,095 10/10/2024
0.4.3.2 617 10/10/2024
0.4.3 1,354 8/12/2024
0.4.2 866 8/12/2024
0.4.1 939 8/9/2024
0.4.0 957 8/8/2024
0.3.0 1,004 7/22/2024
0.2.1 660 3/1/2024
0.2.0 1,295 1/19/2024
0.1.2 443 10/16/2023
0.1.1 376 10/4/2023
0.1.0 928 8/25/2023