Orchestrated multi-agent systems represent the next stage in the evolution of artificial intelligence, where autonomous agents collaborate through structured coordination and communication to achieve complex, shared objectives. This paper consolidates and formalizes the technical composition of such systems, presenting a unified architectural framework that integrates planning, policy enforcement, state management, and quality operations into a coherent orchestration layer. Another primary contribution of this work is the in-depth technical delineation of two complementary communication protocols - the Model Context Protocol, which standardizes how agents access external tools and contextual data, and the Agent2Agent protocol, which governs peer coordination, negotiation, and delegation. Together, these protocols establish an interoperable communication substrate that enables scalable, auditable, and policy-compliant reasoning across distributed agent collectives. Beyond protocol design, the paper details how orchestration logic, governance frameworks, and observability mechanisms collectively sustain system coherence, transparency, and accountability. By synthesizing these elements into a cohesive technical blueprint, this paper provides comprehensive treatments of orchestrated multi-agent systems - bridging conceptual architectures with implementation-ready design principles for enterprise-scale AI ecosystems.

翻译：编排式多智能体系统代表了人工智能发展的新阶段，其中自主智能体通过结构化协调与通信进行协作，以实现复杂的共享目标。本文整合并形式化了此类系统的技术构成，提出了一个统一的架构框架，将规划、策略实施、状态管理与质量运维集成到协调一致的编排层中。本工作的另一主要贡献在于对两种互补通信协议的技术细节进行了深入阐述——Model Context Protocol（标准化智能体访问外部工具与上下文数据的方式）与Agent2Agent protocol（管理对等协调、协商与委托）。这些协议共同建立了可互操作的通信基础，使得分布式智能体集群能够进行可扩展、可审计且符合策略的推理。除协议设计外，本文详细阐述了编排逻辑、治理框架与可观测性机制如何共同维持系统的连贯性、透明度与可问责性。通过将这些要素整合为统一的技术蓝图，本文对编排式多智能体系统进行了全面论述——将概念架构与企业级人工智能生态系统可直接实施的设计原则相衔接。