Khrylx/PyTorch-RL

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1286 stars · 192 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A PyTorch library implementing deep reinforcement learning policy gradient algorithms (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). It features fast Fisher vector product computation for TRPO and multiprocessing support for parallel sample collection.

Use cases

• train a PPO agent on a gym environment
• run TRPO with fast Fisher vector products
• implement A2C for discrete and continuous action spaces
• do imitation learning from expert trajectories with GAIL
• collect RL samples in parallel with multiprocessing
• learn policy gradient algorithms from readable code

When to choose

• you want clean, readable PyTorch implementations of TRPO, PPO, A2C, or GAIL
• you need efficient Fisher vector product computation for TRPO
• you are doing research or learning with OpenAI Gym / MuJoCo environments

When to avoid

• you need a maintained library with recent PyTorch version support
• you want off-the-shelf support for modern RL algorithms like SAC or DQN
• you need production-grade distributed RL training at scale

Facets

library · maturity maintenance

reinforcement-learning machine-learning deep-learning reinforcement-learning machine-learning deep-learning robotics python pytorch policy-gradient trpo ppo a2c gail imitation-learning gym mujoco fisher-vector-product linux macos gpu

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