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Bibliographic Details
Main Author: Dobrovolskyi, Ivan
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2603.22823
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author Dobrovolskyi, Ivan
author_facet Dobrovolskyi, Ivan
contents Context. The problem of comparative evaluation of communication protocols for task orchestration by large language model (LLM) agents is considered. The object of study is the process of interaction between LLM agents and external tools, as well as between autonomous LLM agents, during task orchestration. Objective. The goal of this work is to develop a systematic pilot benchmark comparing tool integration, multi-agent dele-gation, and hybrid architectures for standardized queries at three levels of complexity, and to quantify the advantages and disadvantages in terms of response time, context window consumption, cost, error recovery, and implementation complexity.
format Preprint
id arxiv_https___arxiv_org_abs_2603_22823
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Empirical Comparison of Agent Communication Protocols for Task Orchestration
Dobrovolskyi, Ivan
Artificial Intelligence
Context. The problem of comparative evaluation of communication protocols for task orchestration by large language model (LLM) agents is considered. The object of study is the process of interaction between LLM agents and external tools, as well as between autonomous LLM agents, during task orchestration. Objective. The goal of this work is to develop a systematic pilot benchmark comparing tool integration, multi-agent dele-gation, and hybrid architectures for standardized queries at three levels of complexity, and to quantify the advantages and disadvantages in terms of response time, context window consumption, cost, error recovery, and implementation complexity.
title Empirical Comparison of Agent Communication Protocols for Task Orchestration
topic Artificial Intelligence
url https://arxiv.org/abs/2603.22823