Transfer and Reinforcement Learning Based Production Control

被引：0

作者：

Steinbacher L. ^{[1
]}

Pering E. ^{[1
]}

Freitag M. ^{[1
]}

机构：

[1] BIBA-Bremer Institut für Produktion und Logistik GmbH, Hochschulring 20, Bremen

来源：

ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb | 2022年 / 117卷 / 09期

关键词：

Changeability; Policy Reuse; Production Control; Reinforcement Learning; Transfer Learning;

D O I：

10.1515/zwf-2022-1111

中图分类号：

学科分类号：

摘要：

Constantly increasing complexity and growing information densities in production systems open up potentials for the application of machine learning methods. So-called reinforcement learning is particularly suitable for implementing autonomous agentbased control systems. However, the application of this becomes more difficult in changing production systems. It is shown for the first time that the transfer learning approach is useful for production control systems with reinforcement learning. © 2022 Walter de Gruyter GmbH, Berlin/Boston.

引用

页码：609 / 613

页数：4

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