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Beyond Message Passing: A Semantic View of Agent Communication Protocols

2 Pith papers cite this work. Polarity classification is still indexing.

2 Pith papers citing it
abstract

Agent communication protocols are becoming critical infrastructure for large language model (LLM) systems that must use tools, coordinate with other agents, and operate across heterogeneous environments. This work presents a human-inspired perspective on this emerging landscape by organizing agent communication into three layers: communication, syntactic, and semantic. Under this framework, we systematically analyze 18 representative protocols and compare how they support reliable transport, structured interaction, and meaning-level coordination. Our analysis shows a clear imbalance in current protocol design. Most protocols provide increasingly mature support for transport, streaming, schema definition, and lifecycle management, but offer limited protocol-level mechanisms for clarification, context alignment, and verification. As a result, semantic responsibilities are often pushed into prompts, wrappers, or application-specific orchestration logic, creating hidden interoperability and maintenance costs. To make this gap actionable, we further identify major forms of technical debt in today's protocol ecosystem and distill practical guidance for selecting protocols under different deployment settings. We conclude by outlining a research agenda for interoperable, secure, and semantically robust agent ecosystems that move beyond message passing toward shared understanding.

fields

cs.AI 1 cs.MA 1

years

2026 2

verdicts

UNVERDICTED 2

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representative citing papers

Mesh Inference: A Formal Model of Collective Inference Without a Center

cs.MA · 2026-06-17 · unverdicted · novelty 8.0

Mesh inference allows a network of agents to reach the centralized optimum through local relaxations of a coupled free energy using only admitted observations, with convergence guaranteed by M-matrix properties in the linear-Gaussian regime.

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