RLinf/RLinf

Home for Embodied & Physical AI R&D

A modular high-level library to train embodied AI agents across a variety of tasks and environments.

A lightweight, event-driven multi-agent framework for embodied AI systems.

A framework for Reinforcement Learning research.

Lightweight, GPU-accelerated reinforcement learning for Isaac Lab, mjlab, and Gymnasium.

Scalable, Composable Reinforcement Learning for Real-World Agents with Bedrock AgentCore.

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control

An end-to-end, GPU-accelerated, and modular platform for building generalized Embodied Intelligence.

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