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.
A systematic literature review of predictive maintenance for defence fixed-wing aircraft sustainment and operations.Sensors, 22(18):7070
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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.