← All research projects

Language & agents ICML 2026

LLM-Guided Communication for Cooperative Multi-Agent Reinforcement Learning

Sangjun Bae · Yisak Park · Sanghyeon Lee · Seungyul Han

UNIST · Machine Learning & Intelligent Control Lab

Read the paper ↗

RESEARCH OVERVIEW

Use an LLM to design communication protocols that help partially observable agents reconstruct the shared state.

LMAC refines its communication protocol using a state-awareness criterion. The goal is to improve state reconstruction across agents while reducing differences in what each agent knows.

Publication details & source ↗