UFO^3：编织数字智能体银河

摘要

基于大语言模型（LLM）的智能体正将数字设备从被动工具转变为主动智能协作伙伴。然而现有框架大多局限于单一操作系统或设备，导致跨设备工作流脆弱且高度依赖人工操作。我们提出UFO^3系统，它将异构终端、桌面端、服务器、移动设备与边缘计算节点统一整合为协同编排架构。该系统将用户请求建模为可动态演化的任务星群：即通过显式控制流与数据依赖关系（TaskStarLines）连接的原子化子任务（TaskStars）所构成的分布式有向无环图（DAG）。随着分布式设备的结果流持续输入，任务星群实时演化，支持异步执行、自适应恢复与动态优化。星群协调器在实施动态DAG更新的同时安全异步执行任务，而智能体交互协议（AIP）则通过持久化低延迟通道实现可靠的任务调度与结果流传输。这些设计打破了设备与平台间的传统壁垒，使智能体能够无缝协作并放大集体智能。我们在NebulaBench基准测试集上评估UFO^3，该数据集涵盖5类设备、10个应用场景的55项跨设备任务。实验表明：UFO^3实现83.3%的子任务完成率与70.9%的整体任务成功率，平均并行宽度达1.72，端到端延迟较串行基线降低31%。故障注入实验验证系统在瞬时性与永久性智能体故障下仍能实现优雅降级与恢复。这些结果证明UFO^3能够在异构设备间实现精准、高效、鲁棒的任务编排，将孤立智能体融合为横跨普适计算领域的协同自适应计算架构。

English

Large language model (LLM)-powered agents are transforming digital devices from passive tools into proactive intelligent collaborators. However, most existing frameworks remain confined to a single OS or device, making cross-device workflows brittle and largely manual. We present UFO^3, a system that unifies heterogeneous endpoints, desktops, servers, mobile devices, and edge, into a single orchestration fabric. UFO^3 models each user request as a mutable TaskConstellation: a distributed DAG of atomic subtasks (TaskStars) with explicit control and data dependencies (TaskStarLines). The TaskConstellation continuously evolves as results stream in from distributed devices, enabling asynchronous execution, adaptive recovery, and dynamic optimization. A Constellation Orchestrator} executes tasks safely and asynchronously while applying dynamic DAG updates, and the Agent Interaction Protocol (AIP) provides persistent, low-latency channels for reliable task dispatch and result streaming. These designs dissolve the traditional boundaries between devices and platforms, allowing agents to collaborate seamlessly and amplify their collective intelligence. We evaluate UFO^3 on NebulaBench, a benchmark of 55 cross-device tasks across 5 machines and 10 categories. UFO^3 achieves 83.3% subtask completion, 70.9% task success, exposes parallelism with an average width of 1.72, and reduces end-to-end latency by 31% relative to a sequential baseline. Fault-injection experiments demonstrate graceful degradation and recovery under transient and permanent agent failures. These results show that UFO^3 achieves accurate, efficient, and resilient task orchestration across heterogeneous devices, uniting isolated agents into a coherent, adaptive computing fabric that extends across the landscape of ubiquitous computing.

UFO^3：编织数字智能体银河

UFO^3: Weaving the Digital Agent Galaxy

摘要

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