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Empirical Comparison of Agent Communication Protocols for Task Orchestration

arXiv AI Archived Mar 25, 2026 ✓ Full text saved

arXiv:2603.22823v1 Announce Type: new Abstract: Context. Nowadays, artificial intelligence agent systems are transforming from single-tool interactions to complex multi-agent orchestrations. As a result, two competing communication protocols have emerged: a tool integration protocol that standardizes how agents invoke external tools, and an inter-agent delegation protocol that enables autonomous agents to discover and delegate tasks to one another. Despite widespread industry adoption by dozens

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    Computer Science > Artificial Intelligence [Submitted on 24 Mar 2026] Empirical Comparison of Agent Communication Protocols for Task Orchestration Ivan Dobrovolskyi Context. Nowadays, artificial intelligence agent systems are transforming from single-tool interactions to complex multi-agent orchestrations. As a result, two competing communication protocols have emerged: a tool integration protocol that standardizes how agents invoke external tools, and an inter-agent delegation protocol that enables autonomous agents to discover and delegate tasks to one another. Despite widespread industry adoption by dozens of enterprise partners, no empirical comparison of these protocols exists in the literature. Objective. The goal of this work is to develop the first systematic benchmark comparing tool-integration-only, multi-agent delegation, and hybrid architectures across standardized queries at three complexity levels, and to quantify the trade-offs in response time, context window consumption, monetary cost, error recovery, and implementation complexity. Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2603.22823 [cs.AI]   (or arXiv:2603.22823v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2603.22823 Focus to learn more Submission history From: Ivan Dobrovolskyi [view email] [v1] Tue, 24 Mar 2026 05:50:58 UTC (1,049 KB) Access Paper: view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-03 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv AI
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    ◬ AI & Machine Learning
    Published
    Mar 25, 2026
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    Mar 25, 2026
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