AI RESEARCH

Experience Transfer for Multimodal LLM Agents in Minecraft Game

arXiv CS.AI

ArXi:2604.05533v1 Announce Type: new Multimodal LLM agents operating in complex game environments must continually reuse past experience to solve new tasks efficiently. In this work, we propose Echo, a transfer-oriented memory framework that enables agents to derive actionable knowledge from prior interactions rather than treating memory as a passive repository of static records. To make transfer explicit, Echo decomposes reusable knowledge into five dimensions: structure, attribute, process, function, and interaction.