多重代理在数字孪生实施中的作用：简短调查

IF 23.8 1区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS

ACM Computing Surveys Pub Date : 2024-09-24 DOI:10.1145/3697350

Kalyani Yogeswaranathan, Rem Collier

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引用次数: 0

摘要

近年来，数字孪生（DT）技术已成为一项重要的技术进步。数字孪生是物理资产的数字表示，它反映了物理资产的数据模型、行为以及与其他物理资产的交互。数字孪生旨在实现适应性、无缝数据集成、建模、模拟、自动化和实时数据管理。本文的主要目标是探索代理在数字孪生实施中的作用，试图了解它们的主要使用场景和目的。从我们的角度来看，作为智能实体的代理在实现 DT 功能方面发挥着作用。本文还讨论了数据传输中存在的差距，强调了未来的发展方向，并分析了在数据传输实施中与多代理系统技术相结合的各种技术。最后，本文简要讨论了利用多代理实施智能农业 DT 的架构概述。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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The Role of Multi-Agents in Digital Twin Implementation: Short Survey

In recent years, Digital Twin (DT) technology has emerged as a significant technological advancement. A digital twin is a digital representation of a physical asset that mirrors its data model, behaviour, and interactions with other physical assets. Digital Twin aims to achieve adaptability, seamless data integration, modelling, simulation, automation, and real-time data management. The primary goal of this paper is to explore the role of agents in DT implementations, seeking to understand their predominant usage scenarios and purposes. From our perspective, agents serving as intelligent entities play a role in realising the features of DTs. This paper also discusses the gaps in DT, highlights future directions, and analyses various technologies integrated with multi-agent systems technologies in DT implementations. Finally, the paper briefly discusses an overview of an architecture to implement a DT for smart agriculture with multi-agents.

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来源期刊

ACM Computing Surveys 工程技术-计算机：理论方法

CiteScore

33.20

自引率

0.60%

发文量

372

审稿时长

12 months

期刊介绍： ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.