机器学习如何支持建模和仿真的实践?——综述与未来研究方向

Mahmoud Elbattah
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引用次数: 2

摘要

机器学习(ML)的使用在非常广泛的领域取得了显着的势头。本文旨在为讨论建模与仿真(M&S)与ML的集成提供一个交汇点。讨论提出了赞成M&S实践为什么以及如何以不同的方式利用ML的论点。在此背景下,本文回顾了过去6年在冬季模拟会议、SIGSIM PADS和DS-RT等主要场所发表的重点研究成果。进一步的方面进行了讨论,这可能有助于加强机器学习在M&S领域的利用。总的来说,该研究旨在促进对ML提供的数据驱动知识的利用的潜在想法和推测方向的呈现。
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How can Machine Learning Support the Practice of Modeling and Simulation? —A Review and Directions for Future Research
The use of Machine Learning (ML) has achieved a significant momentum across a very wide range of domains. This paper aims to provide a meeting point for discussing the integration of Modeling and Simulation (M&S) with ML. The discussion presents arguments in favour of why and how the M&S practice can avail of ML in different modalities. In this context, the paper reviews key studies published over the past 6 years in main venues including Winter Simulation Conference, SIGSIM PADS, and DS-RT. Further aspects are discussed, which could help reinforce the utilisation of ML in the M&S arena. In general, the study is conceived to foster the presentation of potential ideas and speculative directions towards availing of data-driven knowledge provided by ML.
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