Riccardo Andrea Izzo

BTGenBot: Behavior Tree Generation for Robotic Tasks with Lightweight LLMs

This paper presents a novel approach to generating behavior trees for robots using lightweight large language models (LLMs) with a maximum of 7 billion parameters. The study demonstrates that it is possible to achieve satisfying results with compact LLMs when fine-tuned on a specific dataset. The ke…