Toni-SM/skrl
Modular Reinforcement Learning (RL) library (implemented in PyTorch, JAX, and NVIDIA Warp) with support for Gymnasium/Gym, NVIDIA Isaac Lab, MuJoCo Playground and other environments
This library helps machine learning engineers and researchers design and train reinforcement learning agents for complex tasks like robotics control or game AI. You provide simulated environments and task definitions, and it outputs trained agent policies that can make decisions to achieve goals within those environments. It's built for practitioners who develop and experiment with advanced AI behaviors.
1,011 stars. Actively maintained with 8 commits in the last 30 days. Available on PyPI.
Use this if you are a machine learning engineer working on reinforcement learning projects and need a flexible, modular toolkit to implement and test various algorithms and environments.
Not ideal if you are looking for a pre-trained, ready-to-deploy AI solution for a specific problem without needing to customize or train agents.
Stars
1,011
Forks
133
Language
Python
License
MIT
Category
Last pushed
Feb 24, 2026
Commits (30d)
8
Dependencies
4
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