hud-evals/hud-python

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.

Research infra for creating RL environments, post-training, and evals.

Evaluate and improve models and agents using environments

Standardized environment infrastructure for Agentic AI development.

An interface library for RL post training with environments.

A construction kit for reinforcement learning environment management.

The absolute trainer to light up AI agents.

Scalable RL for Any Agent and Sandbox.

A customisable 3D platform for agent-based AI research