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MobileAgent

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Basic Information

MobileAgent is an open research and engineering repository that bundles a family of mobile and PC operation assistants and the multi-agent frameworks that power them. It provides multiple related projects and versioned agents, including PC-Agent, Mobile-Agent-E, Mobile-Agent-v2, Mobile-Agent-v3 and the original Mobile-Agent, each focused on automating complex, multi-step tasks across mobile devices and personal computers. The collection emphasizes hierarchical multi-agent collaboration, multi-modal perception for visual input, and practical demos. The README documents demos, video examples, published arXiv papers describing design and evaluation, and links to hosted demos on model hosting platforms. The repo serves as a central place for researchers and developers to explore, reproduce and extend agent architectures for device operation, navigation across apps, and long-horizon task automation.

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4432
App URL
https://github.com/X-PLUG/MobileAgent
Github Repository
https://github.com/X-PLUG/MobileAgent/blob/main/README.md

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App Details

Features
The project family centers on hierarchical multi-agent collaboration where specialized agents coordinate to solve complex tasks. Mobile-Agent-E introduces self-evolution capabilities that leverage past experience to improve performance on long-horizon, reasoning-intensive tasks. PC-Agent is presented as a hierarchical framework for automating PC operations and supports both macOS and Windows. Mobile-Agent variants incorporate multi-modal visual perception for interpreting screenshots and device UIs and effective navigation strategies for mobile control. The repository includes demo artifacts such as videos and hosted interactive demos on model hosting platforms. The README cites multiple technical papers and conference acceptances, highlights improvements in v3 for lower memory overhead and faster reasoning, and lists related multimodal and grounding projects for integration and comparison.
Use Cases
This repository helps researchers, developers and practitioners prototype and evaluate multi-agent assistants for automating tasks on phones and PCs. It supplies reference implementations and demos that illustrate end-to-end behaviors like navigating apps, reading screenshots, and performing multi-step workflows across applications. The hierarchical and collaborative agent designs provide templates for decomposing complex instructions into coordinated subagents, and Mobile-Agent-E demonstrates mechanisms for learning from past runs to improve future performance. PC-Agent offers a base for building cross-platform desktop automation agents. The included papers, videos and hosted demos make it easier to reproduce results, cite the work in academic contexts, and adapt the approaches for new device automation, R&D experiments, or comparative studies.

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