AOHP：一个面向个性化、高效与安全交互的开源操作系统级智能体框架

摘要

AI代理正在推动一种新的软件范式，它们能够自主调用工具、提取信息、管理记忆，并完成跨越应用程序和数据源的任务。然而，大多数现有的终端用户操作系统是为以应用为中心的工作流设计的，对AI代理的原生支持极少。这种不匹配限制了代理的广泛采用，并在传统系统上运行代理时导致执行开销和安全风险。尽管代理原生操作系统的概念正在涌现，但研究界仍缺乏一个开放测试平台来探索代理中介交互所需的架构原语。我们提出AOHP（Android开放集成框架项目）——一个基于安卓开源项目（AOSP）构建的操作系统级代理框架。AOHP的核心设计原则是将代理视为操作系统的一等参与者，实现自适应用户界面和代理友好的运行时环境。AOHP在保留成熟的安卓软件和硬件生态系统的同时，引入了三种面向代理的系统机制：个性化服务组合、高效代理接口和安全的用户信息流。基于覆盖操作系统代理关键能力的挑战性任务的初步实验，AOHP在任务完成率（+21.12%）、执行成本（-51.55%的令牌成本）和安全性策略合规性方面表现出明显优势。

English

AI agents are driving a new software paradigm, with the ability to autonomously call tools, extract information, manage memory, and complete tasks that span applications and data sources. Most existing end-user operating systems, however, are designed for application-centric workflows and offer little native support for AI agents. This mismatch limits the wider adoption of agents and leads to execution overhead and safety risks when running agents on conventional systems. While the concept of agent-native operating systems is emerging, the research community lacks an open testbed to explore the architectural primitives desired for agent-mediated interaction. We present AOHP (Android Open Harness Project), an OS-level agent harness built on the Android Open Source Project (AOSP). The core design principle of AOHP is to treat agents as first-class OS actors, enabling adaptive user interfaces and agent-friendly runtime environments. AOHP preserves the mature Android software and hardware ecosystem while introducing three agent-oriented system mechanisms: personalized service composition, efficient agent interfaces, and secure information flow. Based on preliminary experiments on challenging tasks covering key capabilities of OS agents, AOHP shows clear advantages in task completion (+21.12% completion rate), execution cost (-51.55% token cost), and security-policy compliance.