With the rapid iteration of artificial intelligence technology, multi-agent modeling and simulation technology (MAMS) has developed rapidly and been successfully applied in various fields. This article firstly introduces the concept, technical advantages, research process, and application status of MAMS. It reviews the development of hybrid modeling and simulation combining multi-agent and system dynamics, modeling and simulation of multi-agent reinforcement learning, and modeling and simulation of large-scale multi-agent systems. A comparative analysis is conducted on the general multi-agent modeling and simulation platform. Finally, the existing MAMS platforms and multi-agent technology and tool platforms in the era of large models are introduced. This article systematically summarizes the current research status of MAMS, helping scholars quickly understand the development of MAMS in the AI era, summarizing the advantages and disadvantages of different MAMS platforms, and pointing out the direction for further development of MAMS.
Key words
artificial intelligence /
system dynamics /
reinforcement learning /
large-scale multi-agent
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References
[1] 刘康. 基于多Agent的复杂适应系统建模仿真研究[D].长沙:中南大学, 2011.
[2] 邓宏钟. 基于多智能体的整体建模仿真方法及其应用研究[D].长沙:国防科学技术大学,2002.
[3] 邓宏钟,谭跃进,迟妍.一种复杂系统研究方法—基于多智能体的整体建模仿真方法[J].系统工程,2000 (4):73-78.
[4] 郭戈,康健.具有复杂动力学的多智能体系统分布式优化综述[J].控制与决策,2024,39(7): 2113-2124.
[5] 张帆,武东昊,陈玉萍,等.多智能体深度强化学习的分布式园区综合能源系统经济调度策略[J].电力系统及其自动化学报,2022,34(12):18-26.
[6] Rahmandad H and Sterman J.Heterogeneity and network structure in the dynamics of diffusion: Comparing agent-based and differential equation models[J].Manag.Sci.,2008,54(5):998-1014.
[7] N.Schieritz N and A.Grobler,Emergent structures in supply chains-a study integrating agent-based and system dynamics modeling[C]//in Proc.36th Ann.Hawaii Int.Conf.System Sciences,Big Island,HI,USA,2003:9.
[8] 洪文杰,李肯立,全哲,等.面向神威·太湖之光的PETSc可扩展异构并行算法及其性能优化[J].计算机学报,2017,40(9):2057-2069.
[9] 周锐. 大规模分布式LDA主题模型研究与实现[D].南京:南京大学,2018.
[10] 柴智勇,谷阳阳,史雪莹,等.车载行人预警系统的多智能体交通仿真与效果比较研究[J].武汉理工大学学报(交通科学与工程版),2021,45(2):231-236.
[11] 潘理虎,秦世鹏,李晓文,等.COVID-19病毒防控多智能体仿真模型[J].系统仿真学报,2020,32(11):2244-2257.
[12] 于卫红. 基于JADE平台的多Agent系统开发技术[M].北京:国防工业出版社,2011.
[13] 朱朝磊. 基于多智能体系统的快速路宏微观交通流建模与仿真[D].北京:北京工业大学,2016.
[14] 张俊瑞,王秀华.基于Agent的建模与仿真方法及仿真平台浅析[J].网络安全技术与应用,2016 (12):53-54.
[15] 王宇宾. 基于Repast Simphony平台的建模与仿真技术[J].计算机系统应用,2015,24(10):17-22.
[16] 周甍. 复杂系统分布仿真平台中Agent建模技术的研究与实现[D].长沙:国防科学技术大学,2003.
[17] 赵正平. 人工智能大语言模型和AI芯片的新进展(续)[J].微纳电子技术,2025,62(4):7-39.
[18] 魏巍,曾铮,刘蕾.从DeepSeek突破看我国人工智能产业创新范式、挑战与应对[J].经济纵横,2025(6):102-114.
