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Study on the application of single-agent and multi-agent reinforcement learning to dynamic scheduling in manufacturing environments with growing complexity: Case study on the synthesis of an industrial IoT Test Bed

Research article (Journal of Manufacturing Systems, 2024) · cited 16× · AI/ML
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Study on the application of single-agent and multi-agent reinforcement learning to dynamic scheduling in manufacturing environments with growing complexity: Case study on the synthesis of an industrial IoT Test Bed

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Study on the application of single-agent and multi-agent reinforcement learning to dynamic scheduling in manufacturing environments with growing complexity: Case study on the synthesis of an industrial IoT Test Bed is a scholarly article[1].

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  • Study on the application of single-agent and multi-agent reinforcement learning to dynamic scheduling in manufacturing environments with growing complexity: Case study on the synthesis of an industrial IoT Test Bed's instance of is recorded as scholarly article[2].

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Study on the application of single-agent and multi-agent reinforcement learning to dynamic scheduling in manufacturing environments with growing complexity: Case study on the synthesis of an industrial IoT Test Bed. Retrieved May 24, 2026, from https://4ort.xyz/entity/study-on-the-application-of-single-agent-and-multi-agent-reinforcement-learning-to-dynamic-scheduling-in-manufacturing-e
MLA “Study on the application of single-agent and multi-agent reinforcement learning to dynamic scheduling in manufacturing environments with growing complexity: Case study on the synthesis of an industrial IoT Test Bed.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/study-on-the-application-of-single-agent-and-multi-agent-reinforcement-learning-to-dynamic-scheduling-in-manufacturing-e.
BibTeX @misc{4ortxyz_study-on-the-application-of-single-agent-and-multi-agent-reinforcement-learning-to-dynamic-scheduling-in-manufacturing-e_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Study on the application of single-agent and multi-agent reinforcement learning to dynamic scheduling in manufacturing environments with growing complexity: Case study on the synthesis of an industrial IoT Test Bed}}, year = {2026}, url = {https://4ort.xyz/entity/study-on-the-application-of-single-agent-and-multi-agent-reinforcement-learning-to-dynamic-scheduling-in-manufacturing-e}, note = {Accessed: 2026-05-24}}
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