MobileExperts: A Dynamic Tool-Enabled Agent Team in Mobile Devices
Jiayi Zhang, Chuang Zhao, Yihan Zhao, Zhaoyang Yu, Ming He, Jianping, Fan

TL;DR
MobileExperts introduces a multi-agent, tool-based approach for mobile devices that dynamically assembles expert teams to handle complex tasks efficiently, reducing reasoning costs and improving performance across various task complexities.
Contribution
This work pioneers the integration of tool formulation and multi-agent collaboration in mobile device automation, enhancing handling of complex tasks with reduced reasoning costs.
Findings
Outperforms existing methods across all intelligence levels.
Achieves approximately 22% reduction in reasoning costs.
Validates effectiveness on a new hierarchical intelligence benchmark.
Abstract
The attainment of autonomous operations in mobile computing devices has consistently been a goal of human pursuit. With the development of Large Language Models (LLMs) and Visual Language Models (VLMs), this aspiration is progressively turning into reality. While contemporary research has explored automation of simple tasks on mobile devices via VLMs, there remains significant room for improvement in handling complex tasks and reducing high reasoning costs. In this paper, we introduce MobileExperts, which for the first time introduces tool formulation and multi-agent collaboration to address the aforementioned challenges. More specifically, MobileExperts dynamically assembles teams based on the alignment of agent portraits with the human requirements. Following this, each agent embarks on an independent exploration phase, formulating its tools to evolve into an expert. Lastly, we…
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Taxonomy
TopicsMulti-Agent Systems and Negotiation · Modular Robots and Swarm Intelligence · Mobile Agent-Based Network Management
