AI 中文总结
研究LLM驱动的智能体融入复杂工作流面临的挑战，提出面向智能体的面向服务计算（ASOC）。阐述其六个基本原则，组织五维研究议程，旨在将智能体AI从零散演示转变为可靠的基于服务的系统，为新兴领域提供支撑。
AI 中文摘要
由大语言模型驱动的自主和半自主智能体的迅速出现，正在将软件系统从静态的请求-响应组件重塑为目标导向、自适应且能使用工具的计算参与者。当这些智能体从孤立的认知原型转向复杂的分布式工作流程时，它们面临着面向服务计算领域二十多年来一直在研究的挑战。然而，当今许多智能体人工智能生态系统在临时开发这些基础，缺乏可靠的企业和社会部署所需的工程严谨性。本文介绍了面向智能体的面向服务计算（ASOC），它是一个新的研究和实践领域，涉及将智能体设计为服务、通过自主和半自主智能体编排服务，以及在信任、网络安全、合规、性能和问责制的约束下管理智能体和服务的生态系统。我们阐述了ASOC的六个基本原则，并组织了一个五维研究议程，涵盖智能体服务基础和生命周期工程、组合、编排和互操作性、治理、可观测性和问责制、安全、信任和风险管理，以及评估、认证和智能体QoS。我们认为，服务计算社区特别适合为这个新兴领域提供概念和工程支撑，将智能体人工智能从零散的演示转变为值得人类和组织信任的可靠的基于服务的系统。
英文摘要
The rapid emergence of LLM-powered autonomous and semi-autonomous agents is reshaping software systems from static, request-response components into goal-directed, adaptive, and tool-using computational actors. As these agents move from isolated cognitive prototypes into complex distributed workflows, they confront challenges that the Service-Oriented Computing community has studied for more than two decades: composition, interoperability, quality of service, lifecycle management, governance, security, and trust. Yet much of today's agentic AI ecosystem is developing these foundations ad hoc, without the engineering rigour required for dependable enterprise and societal deployment. This paper introduces Agentic Service-Oriented Computing (ASOC) as a new research and practice area concerned with engineering agents as services, orchestrating services through autonomous and semi-autonomous agents, and governing ecosystems of agents and services under constraints of trust, cybersecurity, compliance, performance, and accountability. We articulate six foundational principles of ASOC (harness-ability, composability, lifecycle engineering, trustworthiness by design, goal-driven orchestration, and observability/accountability) and organise a five-dimensional research agenda spanning: (i) agentic services foundations and lifecycle engineering; (ii) composition, orchestration, and interoperability; (iii) governance, observability, and accountability; (iv) security, trust, and risk management; and (v) evaluation, certification, and Agentic QoS. We argue that the Services Computing community is especially well positioned to provide the conceptual and engineering spine for this emerging field, transforming agentic AI from fragmented demonstrations into dependable, service-based systems worthy of human and organisational trust.
CommentsAccepted at the 2026 IEEE International Conference on Web Services (ICWS); Corresponding author: Prof. Amin Beheshti; DOI 10.1109/ICWS72778.2026.00163
DOI：10.1109/ICWS72778.2026.00163
