将多智能体系统理论融入智能体AI，提升其自主与协作能力。
Agentifying Agentic AI
- 结合BDI架构与机制设计，构建可解释的智能体推理模型。
- 实现灵活自主的同时保证透明、合作与可问责性。
- 适合研究智能体协同与系统治理的学者与工程师。
智能体AI旨在赋予系统持续的自主性、推理与交互能力。为实现这一愿景，必须补充对认知、合作与治理的显式建模。本文认为，自主智能体与多智能体系统（AAMAS）领域发展出的概念工具，如BDI架构、通信协议、机制设计与制度建模，恰好提供了这一基础。通过将自适应的数据驱动方法与结构化的推理与协调模型相结合，我们勾勒出一条路径：使智能体系统不仅具备能力与灵活性，还能实现透明、合作与可问责。最终形成一种融合形式理论与实际自主性的代理视角。
原文摘要 · Abstract (English)
Agentic AI seeks to endow systems with sustained autonomy, reasoning, and interaction capabilities. To realize this vision, its assumptions about agency must be complemented by explicit models of cognition, cooperation, and governance. This paper argues that the conceptual tools developed within the Autonomous Agents and Multi-Agent Systems (AAMAS) community, such as BDI architectures, communication protocols, mechanism design, and institutional modelling, provide precisely such a foundation. By aligning adaptive, data-driven approaches with structured models of reasoning and coordination, we outline a path toward agentic systems that are not only capable and flexible, but also transparent, cooperative, and accountable. The result is a perspective on agency that bridges formal theory and practical autonomy.
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