Title: BusMA: A Bus Communication Substrate for Multi- Agent Systems
Primary area: applications to computer vision, audio, language, and other modalities
Keywords: LLM Agent, Multi Agents

Abstract: Multi-Agent (MA) systems are effective at solving complex tasks that demand advanced planning, tool use, and the synthesis of evidence from multiple sources. Existing  systems typically use Hierarchical Manager-Worker (HMW) structures or Router-based Message Passing (RMP) as their communication protocol to coordinate work. However, they can be restricted due to communication ineffectiveness, since agents cannot directly consult specific colleagues or operate beyond assigned subtasks, and misrouted messages can propagate errors.  
Inspired by bus communication systems in computer systems, we propose BusMA, a bus communication MA framework that allows any agent to address specific peers. Our framework comprises a Chair agent, Worker agents, and a communication bus. Worker agents perform multi-step reason–act–call interactions, enabling targeted requests for help or critique, with the Chair agent synthesizing insights from all agents' communications while adding its own reasoning to produce coherent solutions. The communication bus routes addressable messages and executes requests. Across two frontier LLMs and benchmarks spanning diverse domains, including image understanding, mathematics, and knowledge-based tasks, as well as GAIA with tasks of varied complexity, BusMA consistently achieves the best results, outperforming state-of-the-art multi-agent communication approaches (HMW and RMP-based methods). 
Anonymous code is available at https://anonymous.4open.science/r/Bus-MA-370E.