RLMatrix Documentation
RLMatrix provides a comprehensive reinforcement learning framework for C# developers with performance exceeding Python alternatives.
Key Features
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Comprehensive Algorithm Library: Includes PPO, DQN with all popular modifications (up to C51 and DQN Rainbow), GAIL, and more algorithms on the way
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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 - simply add attributes to your code and the toolkit generates all the reinforcement learning plumbing automatically
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Multi-Head Support: Handle continuous, discrete, and mixed action spaces simultaneously in a single agent
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RNN Integration: Enable recurrent neural networks with a simple option toggle for handling sequential or partial observability problems
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Pure C# Implementation: Built entirely in C# with TorchSharp backend, providing native performance and complete type safety
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Game Engine Ready: Battle-tested in Unity and Godot.
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Superior Performance: Faster and more stable than Python’s stable-baselines, ml-agents, and Godot RL agents
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Multi-Environment Training: Scale learning across parallel (optionally networked) environments
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Industrial-Grade Distributed Training: High-performance, fault-tolerant networked architecture ready for large-scale reinforcement learning deployments
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Transparent Source Code: Clean, well-documented codebase that’s easy to extend or customize. Reinforcement Learning with Dependency Injection!
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Production Reliability: Designed for stability in long-running training sessions with failure tolerance