Machine design is treated as a code generation problem: LLMs choose standard parts and specify how to connect them, making the task well-suited to language models.

The environment includes tasks like throwing a stone far or navigating bumpy terrain, and supports custom goals and environments.

We used it to explore both agentic workflows (no finetuning) and reinforcement learning, trying tasks like building cars and catapults.

It runs 100+ parallel processes on Linux clusters for scalable RL training.

Feedback from the AI, RL, engineering, and game dev communities is welcome.

GitHub: https://github.com/Godheritage/BesiegeField HuggingFace Demo (single-agent): https://huggingface.co/spaces/Godheritage/BesiegeField-Machi...