[论文解读] The Internet of Physical AI Agents: Interoperability, Longevity, and the Cost of Getting It Wrong

Roberto Morabito, Mallik Tatipamula|arXiv (Cornell University)|Mar 16, 2026

IoT and Edge/Fog Computing被引用 0

一句话总结

本论文主张以自治性、开放互操作性、强安全性、可观测性与演化性来设计物理AI代理互联网，避免钙化与高成本，采用受物联网启发的分层架构蓝图。

ABSTRACT

The Internet has evolved by progressively expanding what humanity connects: first computers, then people, and later billions of devices through the Internet of Things (IoT). While IoT succeeded in digitizing perception at scale, it also exposed fundamental limitations, including fragmentation, weak security, limited autonomy, and poor long-term sustainability. Today, advances in edge hardware, sensing, connectivity, and artificial intelligence enable a new phase: the Internet of Physical AI Agents. Unlike IoT devices that primarily sense and report, Physical AI Agents perceive, reason, and act in real time, operating autonomously and cooperatively across safety-critical domains such as disaster response, healthcare, industrial automation, and mobility. However, embedding fast-evolving AI capabilities into long-lived physical infrastructure introduces new architectural risks, particularly around interoperability, lifecycle management, and premature ossification. This article revisits lessons from IoT and Internet evolution, and articulates design principles for building resilient, evolvable, and trustworthy agentic systems. We present an architectural blueprint encompassing agentic identity, secure agent-to-agent communication, semantic interoperability, policy-governed runtimes, and observability-driven governance. We argue that treating evolution, trust, and interoperability as first-class requirements is essential to avoid hard-coding today's assumptions into tomorrow's intelligent infrastructure, and to prevent the high technical and economic cost of getting it wrong.

研究动机与目标

• 推动物联网向在安全关键领域运行的地球尺度物理AI代理互联网的转型。
• 识别架构风险（互操作性、生命周期管理、钙化）并从物联网的不足中学习。
• 提出设计原则与架构底座，以实现长期存在、值得信赖的代理系统。
• 概述使具身智能在大规模可行的使能因素（硬件、AI、连通性、材料）。

提出的方法

• 批判性分析物联网教训，以推导物理AI代理的架构教训与原则。
• 提出包含身份、信任、语义与执行层的分层架构蓝图。
• 主张开放标准与治理以防止碎片化与过早标准化。
• 描述驱动反身自治的使能因素（边缘AI、生成模型、新材料、确定性连接）。
• 阐述设计原则（紧凑设计、具反射的自治、互操作性、设计即安全、治理）。

实验结果

研究问题

• RQ1 在物理AI代理互联网中，哪些架构原则对避免碎片化和钙化至关重要？
• RQ2 如何在数十年内设计出能够随AI与硬件演进的长期存在、安全关键自治？
• RQ3 实现地球尺度物理代理所需的使能技术（边缘AI、材料、确定性网络、生成式AI）有哪些？

主要发现

• 物理AI代理需要长期嵌入式身份与生命周期管理以实现问责与信任。
• 开放、可互操作的框架对实现跨厂商协作、避免孤岛化生态系统至关重要。
• 安全性必须内生且可验证，具备密码凭证、原生安全更新和零信任原则。
• 提出五层架构底座（Agent Substrate、Communication Fabric、Semantic Intelligence、Execution & Control、Governance），以支持反射、协同与安全。
• 生成式AI、边缘AI与新材料使实时反射、语义互操作性与大规模的可持续运行成为可能。