thu-ml/tianshou

Health v2 · maintenance only

Adoption not part of the score

10943 stars · 1333 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Tianshou is a modular, high-performance deep reinforcement learning library built on pure PyTorch and Gymnasium. It offers both low-level hackable interfaces for RL researchers and high-level APIs for training agents, covering online, offline, and experimental multi-agent and model-based RL.

Use cases

• train a deep RL agent on a custom Gymnasium environment
• implement and benchmark policy gradient algorithms like PPO or SAC
• run offline RL experiments with CQL or BCQ
• prototype new RL algorithms with modular PyTorch components
• train DQN variants on Atari environments
• apply imitation learning such as GAIL or behavior cloning

When to choose

• you want a fast, pure-PyTorch RL library with clean, type-safe APIs
• you need broad algorithm coverage across on-policy, off-policy, and offline RL
• you are an RL researcher who needs hackable modular interfaces
• you want well-documented trainers for custom environments

When to avoid

• you need TensorFlow-based RL tooling
• you need production multi-agent RL support (still experimental)
• you depend on Tianshou v1 APIs, since v2 is not backwards compatible
• you want a turnkey RL platform with no coding

Facets

library · maturity active

machine-learning reinforcement-learning deep-learning reinforcement-learning machine-learning deep-learning python cross-platform pytorch gymnasium dqn ppo sac offline-rl imitation-learning multi-agent-rl

Member repositories

For agents

markdown · JSON · MCP: product_card(name="thu-ml/tianshou")