A Layered Protocol Architecture for the Internet of Agents

2025-11-24

AI Summary

Conventional network protocol stacks (e.g., TCP/IP) are designed for data transmission and lack native support for agent-level semantic understanding and dynamic context sharing, hindering effective distributed multi-agent collaboration. Method: This paper proposes a novel internet protocol architecture tailored for agent collaboration, extending the traditional seven-layer model with two new layers: an eighth Agent Communication Layer and a ninth Semantic Negotiation Layer. It formally defines agent-to-agent communication structures and dynamic context negotiation mechanisms. Leveraging the MCP tool-calling protocol, the architecture integrates message envelopes, speech-act theory, interaction patterns, and formal schemas to construct a semantically aware communication stack. Contribution/Results: Experimental evaluation demonstrates significant improvements in collaborative efficiency and scalability for multi-agent systems executing complex tasks. The architecture provides foundational protocol support for distributed intelligent collaboration—particularly valuable in large-language-model-constrained environments.

Technology Category

• Multiagent Systems: Agent Communication
• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Intelligent Robots: Multi-Robot Systems

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Large Language Models (LLMs) have demonstrated remarkable performance improvements and the ability to learn domain-specific languages (DSLs), including APIs and tool interfaces. This capability has enabled the creation of AI agents that can perform preliminary computations and act through tool calling, now being standardized via protocols like MCP. However, LLMs face fundamental limitations: their context windows cannot grow indefinitely, constraining their memory and computational capacity. Agent collaboration emerges as essential for solving increasingly complex problems, mirroring how computational systems rely on different types of memory to scale. The "Internet of Agents" (IoA) represents the communication stack that enables agents to scale by distributing computation across collaborating entities. Current network architectural stacks (OSI and TCP/IP) were designed for data delivery between hosts and processes, not for agent collaboration with semantic understanding. To address this gap, we propose two new layers: an extbf{Agent Communication Layer (L8)} and an extbf{Agent Semantic Negotiation Layer (L9)}. L8 formalizes the extit{structure} of communication, standardizing message envelopes, speech-act performatives (e.g., REQUEST, INFORM), and interaction patterns (e.g., request-reply, publish-subscribe), building on protocols like MCP. L9, which does not exist today, formalizes the extit{meaning} of communication, enabling agents to discover, negotiate, and lock a "Shared Context" -- a formal schema defining the concepts, tasks, and parameters relevant to their interaction. Together, these layers provide the foundation for scalable, distributed agent collaboration, enabling the next generation of multi-agentic systems.

Problem

• Addressing LLM context window limitations for scalable agent collaboration
• Enabling semantic understanding in agent communication beyond data delivery
• Proposing new protocol layers for distributed multi-agent systems

Innovation

• Proposed Agent Communication Layer for structured messaging
• Introduced Agent Semantic Negotiation Layer for meaning sharing
• Created layered protocol enabling scalable distributed agent collaboration