A Survey on Agentic Service Ecosystems: Measurement, Analysis, and Optimization
Xuwen Zhang, Xiao Xue, Xia Xie, Qun Ma, Xiangning Yu, Deyu Zhou, Yifan Wang, Ming Zhang

TL;DR
This paper reviews and proposes a comprehensive framework for measuring, analyzing, and optimizing swarm intelligence emergence in complex agentic service ecosystems, addressing current research gaps and providing practical tools.
Contribution
It introduces a unified framework with three steps—measurement, analysis, and optimization—for understanding and enhancing swarm intelligence in agentic ecosystems.
Findings
Framework clarifies cyclical mechanisms of emergence
Identifies key quantitative criteria for swarm intelligence
Analyzes strengths and limitations of existing technologies
Abstract
The Agentic Service Ecosystem consists of heterogeneous autonomous agents (e.g., intelligent machines, humans, and human-machine hybrid systems) that interact through resource exchange and service co-creation. These agents, with distinct behaviors and motivations, exhibit autonomous perception, reasoning, and action capabilities, which increase system complexity and make traditional linear analysis methods inadequate. Swarm intelligence, characterized by decentralization, self-organization, emergence, and dynamic adaptability, offers a novel theoretical lens and methodology for understanding and optimizing such ecosystems. However, current research, owing to fragmented perspectives and cross-ecosystem differences, fails to comprehensively capture the complexity of swarm-intelligence emergence in agentic contexts. The lack of a unified methodology further limits the depth and systematic…
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Taxonomy
TopicsModular Robots and Swarm Intelligence · Robotics and Automated Systems · Digital Transformation in Industry
