How can LLMs learn actions in new environments?
SynWorld: Virtual Scenario Synthesis for Agentic Action Knowledge Refinement
April 7, 2025
https://arxiv.org/pdf/2504.03561SynWorld helps LLMs learn how to use tools and navigate new environments by creating virtual scenarios and letting the LLM explore different action sequences within them using a Monte Carlo Tree Search. This improves the LLM's understanding of tool usage and how to plan actions effectively, especially for complex, multi-step tasks. It addresses the challenge of LLMs struggling in unfamiliar environments or with undefined action spaces by letting them learn and refine their action knowledge through simulated experience. This allows LLMs to generalize their knowledge to real-world situations, effectively optimizing tool descriptions and planning workflows.