AIMay 8, 2025

EcoAgent: An Efficient Device-Cloud Collaborative Multi-Agent Framework for Mobile Automation

arXiv:2505.05440v36 citationsh-index: 8Has Code
Originality Incremental advance
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This work addresses efficiency and privacy challenges in mobile automation for users and developers, representing an incremental improvement over existing multi-agent systems.

The paper tackles the problem of high latency and privacy issues in cloud-based mobile multi-agent systems by proposing EcoAgent, a device-cloud collaborative framework that matches the task success rates of fully cloud-based agents while reducing resource consumption and response latency.

To tackle increasingly complex tasks, recent research on mobile agents has shifted towards multi-agent collaboration. Current mobile multi-agent systems are primarily deployed in the cloud, leading to high latency and operational costs. A straightforward idea is to deploy a device-cloud collaborative multi-agent system, which is nontrivial, as directly extending existing systems introduces new challenges: (1) reliance on cloud-side verification requires uploading mobile screenshots, compromising user privacy; and (2) open-loop cooperation lacking device-to-cloud feedback, underutilizing device resources and increasing latency. To overcome these limitations, we propose EcoAgent, a closed-loop device-cloud collaborative multi-agent framework designed for privacy-aware, efficient, and responsive mobile automation. EcoAgent integrates a novel reasoning approach, Dual-ReACT, into the cloud-based Planning Agent, fully exploiting cloud reasoning to compensate for limited on-device capacity, thereby enabling device-side verification and lightweight feedback. Furthermore, the device-based Observation Agent leverages a Pre-understanding Module to summarize screen content into concise textual descriptions, significantly reducing token usage and device-cloud communication overhead while preserving privacy. Experiments on AndroidWorld demonstrate that EcoAgent matches the task success rates of fully cloud-based agents, while reducing resource consumption and response latency. Our project is available here: https://github.com/Yi-Biao/EcoAgent.

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