The Applicability of Reinforcement Learning Methods in the Development of Industry 4.0 Applications. (30th November 2021)

• Record Type: Journal Article
• Authors: Kegyes, Tamás; Süle, Zoltán; Abonyi, János
• Other Names: Andrea Murari Academic Editor.
• Is Part Of: Complexity. Volume 2021(2021)
• Publication Date: 2021-11-30
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2021/7179374
• Languages: English
• ISSNs: 1076-2787

Abstract

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.