Towards Self-X cognitive manufacturing network: An industrial knowledge graph-based multi-agent reinforcement learning approach
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Title
Towards Self-X cognitive manufacturing network: An industrial knowledge graph-based multi-agent reinforcement learning approach
Authors
Keywords
Industrial knowledge graph, Graph embedding, Cognitive manufacturing, Graph neural network, Reinforcement learning
Journal
JOURNAL OF MANUFACTURING SYSTEMS
Volume 61, Issue -, Pages 16-26
Publisher
Elsevier BV
Online
2021-08-12
DOI
10.1016/j.jmsy.2021.08.002
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- (2019) Zuoxu Wang et al. ADVANCED ENGINEERING INFORMATICS
- A graph-based context-aware requirement elicitation approach in smart product-service systems
- (2019) Zuoxu Wang et al. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- Contextual self-organizing of manufacturing process for mass individualization: a cyber-physical-social system approach
- (2018) Jiewu Leng et al. Enterprise Information Systems
- Exploiting semantic similarity for named entity disambiguation in knowledge graphs
- (2018) Ganggao Zhu et al. EXPERT SYSTEMS WITH APPLICATIONS
- Industrial Internet of Things: Challenges, Opportunities, and Directions
- (2018) Emiliano Sisinni et al. IEEE Transactions on Industrial Informatics
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- (2011) Xun Xu ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
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- (2010) M.M. Tseng et al. CIRP ANNALS-MANUFACTURING TECHNOLOGY
- Ontology-based reconfiguration agent for intelligent mechatronic systems in flexible manufacturing
- (2010) Yazen Alsafi et al. ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
- Community detection in graphs
- (2009) Santo Fortunato PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS
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