Smart Commander applies hierarchical reinforcement learning to optimize sequential maintenance, sortie generation, and resource allocation decisions across a military aircraft fleet, outperforming flat DRL and rule-based methods in a custom simulation.
Remaining useful life prediction using a novel feature-attention-based end-to-end approach.IEEE Transactions on Industrial Informatics, 17(2):1197–1207
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Smart Commander: A Hierarchical Reinforcement Learning Framework for Fleet-Level PHM Decision Optimization
Smart Commander applies hierarchical reinforcement learning to optimize sequential maintenance, sortie generation, and resource allocation decisions across a military aircraft fleet, outperforming flat DRL and rule-based methods in a custom simulation.