将智能代理纳入服务计算框架,构建可信赖的自主系统。
Agentic Service-Oriented Computing: A Manifesto for the Next Frontier of Service-Oriented Computing

- 提出智能代理服务计算(ASOC)新范式,以服务化方式组织智能体
- 定义六项核心原则与五维研究方向,覆盖全生命周期管理
- 适合关注可信智能系统、企业级AI部署的研究者与工程师
大语言模型驱动的自主与半自主智能体正重塑软件系统,使其从静态请求-响应组件转变为目标导向、自适应且能使用工具的计算主体。随着这些智能体从孤立的认知原型演变为复杂的分布式工作流,它们面临服务计算领域长期研究的挑战:组合性、互操作性、服务质量、生命周期管理、治理、安全与信任。然而当前多数智能体生态在基础建设上缺乏工程严谨性,难以支撑企业与社会级部署。本文提出智能代理服务计算(ASOC),聚焦于将智能体作为服务进行工程化,通过自主或半自主智能体编排服务,并在信任、网络安全、合规性、性能与问责约束下治理智能体与服务生态系统。我们提出六项基本原则(可利用性、可组合性、生命周期工程、设计即可信、目标驱动编排、可观测性与问责),并构建涵盖五个维度的研究议程:(i) 智能代理服务基础与生命周期工程;(ii) 组合、编排与互操作性;(iii) 治理、可观测性与问责;(iv) 安全、信任与风险管理;(v) 评估、认证与智能代理QoS。我们认为服务计算领域具备提供该新兴领域概念与工程骨架的独特优势,推动智能代理从零散演示走向可信赖的服务化系统。
原文摘要 · Abstract (English)
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.
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