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TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. TorchRL provides PyTorch and python-first, low and high-level abstractions for RL that are intended to be efficient, modular, documented, and properly tested. The code is aimed at supporting research in RL. Most of it is written in Python in a highly modular way, such that researchers can easily swap components, transform them, or write new ones with little effort.
Features
- Designed with Python as the primary language for ease of use and flexibility
- Optimized for performance to support demanding RL research applications
- Highly modular architecture allows for easy swapping, transformation, or creation of new components
- Thorough documentation ensures that users can quickly understand and utilize the library
- Documentation available
- Rigorously tested to ensure reliability and stability
- Provides a set of highly reusable functions for cost functions, returns, and data processing
Project Samples
Categories
Machine Learning, Reinforcement Learning Frameworks, Reinforcement Learning Libraries, Reinforcement Learning AlgorithmsLicense
MIT LicenseFollow TorchRL
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