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AI智能体的自然语言交互协议与标准

The Natural Language Interaction Protocol and Standard for AI Agents

Luyi Xing, Rasit Onur Topaloglu, Ranjan Sinha, Abhay Ratnaparkhi, Samuel Ndichu, Christopher Nguyen, Anindita Das, Tom Sheffler, Mohamed Rahouti, Zichuan Li, Xiaojing Liao, Sanjay Aiyagari

arXiv 2609.04135首次发表:更新:

发表机构

University of Illinois at Urbana-Champaign; Marist University; IBM; Aitomatic, Inc.; Fordham University(伊利诺伊大学厄巴纳-香槟分校; 玛里斯大学; 国际商业机器公司; 艾托马蒂克公司; 福特汉姆大学)

机构由 AI 辅助整理,请以论文原文为准。

AI 中文总结

本文介绍了由多方开发并经Ecma International标准化的NLIP协议,解决异构AI智能体的互操作问题,阐述其设计、实现及与其他协议的关系。

AI 中文摘要

AI智能体正被越来越多地开发并部署在采用异构智能体开发框架、AI模型、工具接口、协议及执行环境的各类组织中。为实现其潜在的社会与商业影响,这些智能体必须能够通过通用通信协议实现互操作。由企业与高校的研究人员及从业者共同开发、经Ecma International标准化的自然语言交互协议(Natural Language Interaction Protocol,NLIP),通过定义基于标准的AI智能体交互应用层协议满足了这一需求。NLIP提供了轻量级语义消息信封,可通过HTTP/HTTPS、WebSocket、AMQP等现有传输层承载,同时允许支持NLIP的智能体与网关在客户端、智能体、本地上下文存储、本体、工具、企业服务及异构底层协议间进行适配。本文阐述了NLIP的动机与设计原理、消息模型与传输绑定、设计安全考量、参考实现、代表性应用、采用信号,以及其与MCP、A2A等新兴智能体协议的关系。

英文摘要

AI agents are increasingly being developed and deployed across organizations using heterogeneous agent-development frameworks, AI models, tool interfaces, protocols, and execution environments. To realize their potential social and business impact, these agents must be able to interoperate through a common communication protocol. The Natural Language Interaction Protocol (NLIP), developed by researchers and practitioners across companies and universities and standardized by Ecma International, addresses this need by defining a standards-based application-layer protocol for AI-agent interaction. NLIP provides a lightweight semantic message envelope that can be carried over existing transports such as HTTP/HTTPS, WebSocket, and AMQP, while allowing NLIP-aware agents and gateways to adapt between clients, agents, local context stores, ontologies, tools, enterprise services, and heterogeneous underlying protocols. This paper presents the motivation and design rationale of NLIP, its message model and transport bindings, security-by-design considerations, reference implementation, representative applications, adoption signals, and relationship to emerging agent protocols such as MCP and A2A.

CommentsAccepted by ACM AI Summit 2026

论文原文

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