[1]张万鹏,谭思雨,谷学强,等.复杂系统智能演进技术综述[J].智能系统学报,2026,21(5):1084-1105.[doi:10.11992/tis.202510041]
　ZHANG Wanpeng,TAN Siyu,GU Xueqiang,et al.Review of intelligent evolution technology for complex systems[J].CAAI transactions on intelligent systems,2026,21(5):1084-1105.[doi:10.11992/tis.202510041]
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复杂系统智能演进技术综述

《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷: 21 期数: 2026年第5期 页码: 1084-1105 栏目: 综述 出版日期: 2026-09-05
Title:
Review of intelligent evolution technology for complex systems
作者:
张万鹏1, 谭思雨2, 谷学强1, 王尧1, 王笛咏2, 朱莎莎2
1. 国防科技大学 智能科学学院, 湖南 长沙 410073;
2. 湖南先进技术研究院, 湖南 长沙 410205
Author(s):
ZHANG Wanpeng1, TAN Siyu2, GU Xueqiang1, WANG Yao1, WANG Diyong2, ZHU Shasha2
1. College of Intelligent Sciences, National University of Defense Technology, Changsha 410073, China;
2. Hunan Institute of Advanced Technology, Changsha 410205, China
关键词:
人工智能; 复杂系统; 智能演进; 学习优化反馈; 大数据决策; 边缘智能; 多智能体协同; 自适应演进
Keywords:
artificial intelligence; complex systems; intelligent evolution; learning optimization feedback; big data decision making; edge intelligence; multi-agent collaboration; adaptive evolution
分类号:
TP18
DOI:
10.11992/tis.202510041
摘要:
复杂系统作为大量局部自治系统持续集成、相互耦合关联而成的大型系统，其智能演进的基本思想是利用智能技术实现系统持续赋能，以人工智能为驱动、以信息大数据为支撑下的复杂系统已实现了技术迭代和场景更新的多轮演进。本文聚焦人工智能复杂系统，首先从智能演进基础理论进行剖析，提炼智能演进概念，围绕复杂系统感知层、计算层、优化层提出演进技术融合框架；其次重点对大数据决策、边缘智能、多智能体协同、自适应演进四大智能关键技术进行总结，概述以上技术在复杂系统内部的关键支撑作用及技术发展演进路线；最后对未来人工智能驱动下的复杂系统演进方向进行了展望。本文可为下一代人工智能复杂系统的发展路径提供理论基础。
Abstract:
As a large-scale system that continuously integrates and couples a large number of local autonomous systems, the basic idea of intelligent evolution of complex systems is to use intelligent technology to achieve continuous empowerment of the system. The complex system driven by artificial intelligence and supported by big data has achieved multiple rounds of technological iteration and scene updates. This article focuses on complex artificial intelligence systems. Firstly, it analyzes the basic theories of intelligent evolution, refine the concept of intelligent evolution, and propose an evolution technology integration framework centered around the perception layer, computing layer, and optimization layer of complex systems. and summarizes the four key evolution technologies of big data decision-making, edge intelligence, multi-agent collaboration, and adaptive evolution, summarize the crucial supporting role of the above technologies within complex systems and the development and evolution path of these technologies. It also looks forward to the future direction of complex system evolution driven by artificial intelligence. This article can provide theoretical support for the development path of the next generation of artificial intelligence complex systems.
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备注/Memo

收稿日期:2025-10-30。
作者简介:张万鹏，研究员，博士生导师，主要研究方向为人工智能、智能规划与决策。主持和参与重大课题研究项目 10 余项，发表学术论文 10 余篇，出版专著/教材 6 部。E-mail：wpzhang@nudt.edu.cn。;谭思雨，助理研究员，主要研究方向为人工智能、系统智能演进，获国家发明专利授权 2 项，发表学术论文2篇。E-mail：tansiyu0313@163.com。;谷学强，副研究员，主要研究方向为智能规划与决策、边缘智能。获国家发明专利授权 10 余项，发表学术论文30 余篇。E-mail：xueqiang_gu@nudt.edu.cn。
通讯作者:谷学强. E-mail：xueqiang_gu@nudt.edu.cn

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