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• W4313472918 abstract "Agile product development cycles and re-configurable Industrial Internet of Things (IIoT) allow more flexible and resilient industrial production systems that can handle a broader range of challenges and improve their productivity. Reinforcement Learning (RL) was shown to be able to support industrial production systems to be flexible and resilient to respond to changes in real time. This study examines the use of RL in a wide range of adaptive cognitive systems with IIoT-edges in manufacturing processes. We propose a cognitive adaptive system using IIoT with RL (CAS-IIoT-RL) and our experimental analysis showed that the proposed model showed improvements with adaptive and dynamic decision controls in challenging industrial environments." @default.
• W4313472918 created "2023-01-06" @default.
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• W4313472918 date "2023-01-01" @default.
• W4313472918 modified "2023-09-25" @default.
• W4313472918 title "Cognitive Adaptive Systems for Industrial Internet of Things Using Reinforcement Algorithm" @default.
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• W4313472918 doi "https://doi.org/10.3390/electronics12010217" @default.
• W4313472918 hasPublicationYear "2023" @default.
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