Tianshou
An elegant PyTorch-based deep reinforcement learning library with modular APIs for both research and application development.
What is Tianshou?
Tianshou is a deep reinforcement learning library built on PyTorch that provides a modular framework for developing, training, and evaluating RL agents. It solves the problem of complex, inflexible codebases in RL by offering both user-friendly high-level APIs for applications and hackable low-level interfaces for algorithm research, supporting a wide range of algorithms from online DQN to offline CQL.
Reinforcement learning researchers seeking a flexible, type-safe library for algorithm development, and practitioners needing a high-performance, easy-to-use toolkit for applying RL to custom environments.
Developers choose Tianshou for its clean separation between algorithms and policies, extensive algorithm coverage, and dual API design that balances ease of use with research flexibility, all while maintaining high software engineering standards with thorough testing and documentation.
Overview
An elegant PyTorch deep reinforcement learning library.
Use Cases
Best For
- Implementing and experimenting with novel reinforcement learning algorithms
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