arXiv cs.AI· Yuning Chen, Hongda Zhang, Linqiang Hu, Ziqing Zhou, Yi Liu, Zhao Huang, Ding Zhou, Haining Xu·· 2 小时前AI 评分29
智能制造中的自主性与协调性：递归自主智能体（RAA）框架
Autonomy and Coordination in Intelligent Manufacturing: A Recursive Autonomous Agent Framework
AI 导读
一篇 arXiv 论文从复杂自适应系统视角分析生产组织中的智能，识别出个体自主与集体协调两种耦合机制。作者据此提出递归自主智能体（RAA）框架，用目标契约界定局部目标与运行边界，用能力契约支持生产单元的选择与组合，通过通用接口使设备、产线和工厂可作为单元参与更大规模组织，为下一代智能制造提供工程化路径。
正文 · 原文
Abstract:Intelligent production requires systems to make decisions and organize work according to production goals and operating conditions. It also requires continuous adjustment through feedback. This paper analyzes intelligence in human production organizations from a complex adaptive systems (CAS) perspective. The analysis identifies two coupled mechanisms: individual autonomy and collective coordination. Individual autonomy enables actors to form local decisions using available information. Collective coordination aligns these decisions with shared goals and joint constraints. Learning and adaptation improve both mechanisms over time. A production-system model formalizes how local decision rules and coordination jointly form system decisions. On this basis, we propose the Recursive Autonomous Agent (RAA) framework, which combines goal-driven autonomous agents with a recursive organizational structure. Goal contracts define local objectives and operating boundaries, while capability contracts support the selection and composition of production units. Common interfaces allow coordinated groups to participate as units in larger organizations, connecting equipment, production lines, and factories. RAA thus provides an engineering approach to next-generation intelligent manufacturing, translating the requirements of intelligence, openness, and system-wide integration into mechanisms for autonomous and coordinated production.
| Subjects: | Artificial Intelligence (cs.AI); Machine Learning (cs.LG) |
| Cite as: | arXiv:2611.05828 [cs.AI] |
| (or arXiv:2611.05828v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2611.05828 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Hongda Zhang [view email]
[v1]
Wed, 4 Nov 2026 02:11:50 UTC (2,099 KB)
来源：arXiv cs.AI · arxiv.org