The Applicability of Reinforcement Learning Methods in the Development of Industry 4.0 Applications

Author:

Kegyes Tamás1ORCID,Süle Zoltán2ORCID,Abonyi János1ORCID

Affiliation:

1. MTA-PE “Lendület” Complex Systems Monitoring Research Group, University of Pannonia, Veszprém, Hungary

2. University of Pannonia, Veszprém, Hungary

Abstract

Reinforcement learning (RL) methods can successfully solve complex optimization problems. Our article gives a systematic overview of major types of RL methods, their applications at the field of Industry 4.0 solutions, and it provides methodological guidelines to determine the right approach that can be fitted better to the different problems, and moreover, it can be a point of reference for R&D projects and further researches.

Publisher

Hindawi Limited

Subject

Multidisciplinary,General Computer Science

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Reinforcement Learning in Process Industries: Review and Perspective;IEEE/CAA Journal of Automatica Sinica;2024-02

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3. Smart mobile robot fleet management based on hierarchical multi-agent deep Q network towards intelligent manufacturing;Engineering Applications of Artificial Intelligence;2023-09

4. Reinforcement learning for energy-efficient control of parallel and identical machines;CIRP Journal of Manufacturing Science and Technology;2023-09

5. Development of Product Quality with Enhanced Productivity in Industry 4.0 with AI Driven Automation and Robotic Technology;2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS);2023-08-23

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