C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
Evaluate and improve models and agents using environments
An RL-Gym for Challenge Problems in Data-Driven Modeling and Control of Fluid Dynamics.
Creating realistic RL environments requires collaboration between researchers, engineers, and domain experts across many dimensions: artifacts, environments tools, dynamism of the environment, reproducibility, and more. There is no open source framework for building these environments effectively. Until now.
Lightweight, GPU-accelerated reinforcement learning for Isaac Lab, mjlab, and Gymnasium.