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Deep Reinforcement Learning in C#

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# 🚀 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](https://img.shields.io/nuget/v/RLMatrix.svg?label=RLMatrix)](https://www.nuget.org/packages/RLMatrix/)
[![TorchSharp](https://img.shields.io/badge/Made%20With-TorchSharp-8A2BE2)](https://github.com/dotnet/TorchSharp)
[![Discord](https://img.shields.io/discord/1273966278381670511?label=Discord&logo=discord&logoColor=white)](https://discord.gg/ppgr44rBHn)

## 💬 Get in Touch

- **Discord**: Join our [community server](https://discord.gg/ppgr44rBHn) 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](https://www.rlmatrix.net/beginner/gettingstarted/) 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](https://github.com/asieradzk/CartPoleForTesting).

## ✨ 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](https://i.imgur.com/jTKghOP.gif)

## 🗺️ 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 [MIT License](https://github.com/asieradzk/RL_Matrix/blob/master/LICENSE.md).

# 🚀 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](https://img.shields.io/nuget/v/RLMatrix.svg?label=RLMatrix)](https://www.nuget.org/packages/RLMatrix/)
[![TorchSharp](https://img.shields.io/badge/Made%20With-TorchSharp-8A2BE2)](https://github.com/dotnet/TorchSharp)
[![Discord](https://img.shields.io/discord/1273966278381670511?label=Discord&logo=discord&logoColor=white)](https://discord.gg/ppgr44rBHn)
## 💬 联系我们
- **Discord**: 加入我们的[社区服务器](https://discord.gg/ppgr44rBHn)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](https://www.rlmatrix.net/beginner/gettingstarted/)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](https://github.com/asieradzk/CartPoleForTesting)。
## ✨ 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](https://i.imgur.com/jTKghOP.gif)
## 🗺️ 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[MIT许可证](https://github.com/asieradzk/RL_Matrix/blob/master/LICENSE.md)。

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