EcoAgent: An Efficient Device-Cloud Collaborative Multi-Agent Framework for Mobile Automation
Abstract
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.
Fields of Study & Subjects
Advanced Malware Detection Techniques
Multi-Agent Systems and Negotiation
Mobile Agent-Based Network Management
Publication details
- Journal / source
- Proceedings of the AAAI Conference on Artificial Intelligence
- Publisher
- Association for the Advancement of Artificial Intelligence (AAAI)
- Volume
- 40
- Issue
- 35
- Pages
- 29838–29846
- Publication date
- 14 March 2026