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 RLMatrix.Toolkit 0.5.2.3 

dotnet add package RLMatrix.Toolkit --version 0.5.2.3
 
 
NuGet\Install-Package RLMatrix.Toolkit -Version 0.5.2.3
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.Toolkit" Version="0.5.2.3">
 <PrivateAssets>all</PrivateAssets>
 <IncludeAssets>runtime; build; native; contentfiles; analyzers</IncludeAssets>
</PackageReference>
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
<PackageVersion Include="RLMatrix.Toolkit" Version="0.5.2.3" />
 


 Directory.Packages.props
 

 

 
<PackageReference Include="RLMatrix.Toolkit">
 <PrivateAssets>all</PrivateAssets>
 <IncludeAssets>runtime; build; native; contentfiles; analyzers</IncludeAssets>
</PackageReference>
 


 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.Toolkit --version 0.5.2.3
The NuGet Team does not provide support for this client. Please contact its maintainers for support. 
#r "nuget: RLMatrix.Toolkit, 0.5.2.3"
#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. 
#:package RLMatrix.Toolkit@0.5.2.3
#:package directive can be used in C# file-based apps starting in .NET 10 preview 4. Copy this into a .cs file before any lines of code to reference the package. 
#addin nuget:?package=RLMatrix.Toolkit&version=0.5.2.3
 


 Install as a Cake Addin
 

 

 
#tool nuget:?package=RLMatrix.Toolkit&version=0.5.2.3
 


 Install as a Cake Tool
The NuGet Team does not provide support for this client. Please contact its maintainers for support.

👁 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

There are no supported framework assets in this package.

Learn more about Target Frameworks and .NET Standard.

  • .NETStandard 2.0

    • No dependencies.

NuGet packages

This package is not used by any NuGet packages.

GitHub repositories (1)

Showing the top 1 popular GitHub repositories that depend on RLMatrix.Toolkit:

Repository Stars
lindexi/lindexi_gd
博客用到的代码
Version Downloads Last Updated
0.5.2.3 380 7/4/2025
0.5.2.2 189 7/4/2025
0.5.2.1 185 7/4/2025
0.5.2 249 7/2/2025
0.4.3.8 442 2/12/2025
0.4.3.3 227 10/10/2024
0.4.3.2 193 9/24/2024
0.4.3 181 9/23/2024