Spine-Branch Coordination for Multi-agent Computer Use

2026-08-22

AI Summary

为解决多代理计算机使用中的虚拟机状态无法合并问题，提出了一种脊柱-分支协调框架，通过分解任务并行执行，提高成功率同时降低成本。

Abstract

Computer use agents (CUAs) are increasingly deployed as multi-agent systems that decompose a task into multiple subtasks executed across parallel virtual machines (VMs). However, a critical physical bottleneck is that the state of two VMs cannot be merged. Previous systems handle this ad-hoc rather than treating it as a first-class concern. We propose Spine-Branch Coordination for multi-agent computer use, a framework that decomposes a task into a "spine-branch" graph, where the spine carries the main task flow with continuous VM state and branch tasks execute in parallel to collect information the spine needs to complete the task. Branch VMs are discarded once their tasks finish, so no VM merging ever occurs. Experiments show that on 200 long-horizon tasks from Odysseys and across three CUA backbones, Spine-Branch improves success rate over the baseline system by 6.0% to 16.5%, while reducing per-task cost by 34% to 70%, indicating that explicitly modeling VM-state merging constraint enables multi-agent computer use to scale efficiently.

Problem

• multi-agent systems
• virtual machines
• VM-state merging
• task decomposition

Innovation

• Spine-Branch Coordination
• multi-agent systems
• VM-state merging constraint
• task decomposition