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Open access Aug 2026

Knowledge-Guided Graph iTransformer Enhanced by Reinforcement Learning for Industrial Fault Diagnosis

Complex industrial processes are characterized by strong coupling, nonlinear interactions, and dynamic causal dependencies between variables, posing significant challenges for accurate fault diagnosis. Conventional data-driven methods often fail to effectively exploit structural prior knowledge, limiting their ability...

Runhan Liu, Zilong Liu, Zhudan Chen et al. · 0 citations
2026

STAGE: Spatio-Temporal Aggregation via Graph Embedding for Multi-Agent Reinforcement Learning in Industrial Optimization

Industrial multi-agent coordination requires distributed subsystems to collaborate under heterogeneous relationship structures whose relative importance shifts across operational contexts—physical constraints dominate startup while operational hierarchies govern steady-state. Existing multi-agent reinforcement learning...

Chiqiang Liu, Dazi Li, Xin Xu · 0 citations

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