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

Tamás Kegyes | Zendy; Zoltán Süle | Zendy; János Abonyi | Zendy

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

Author(s) -

Tamás Kegyes,

Zoltán Süle,

János Abonyi

Publication year - 2021

Publication title -

complexity

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.447

H-Index - 61

eISSN - 1099-0526

pISSN - 1076-2787

DOI - 10.1155/2021/7179374

Subject(s) - reinforcement learning , computer science , reinforcement , field (mathematics) , point (geometry) , development (topology) , artificial intelligence , management science , industrial engineering , machine learning , mathematics , engineering , mathematical analysis , geometry , structural engineering , pure mathematics

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.

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