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Reinforcement Learned Adversarial Agent (ReLAA) for Active Fault Detection and Prediction in Space Habitats

Space Sciences

Reinforcement Learned Adversarial Agent (ReLAA) for Active Fault Detection and Prediction in Space Habitats

M. Overlin, S. Iannucci, et al.

Explore the cutting-edge research by Matthew Overlin, Steven Iannucci, Bradly Wilkins, Alexander McBain, and Jason Provancher, introducing the revolutionary reinforcement learning adversarial agent (ReLAA) designed for enhancing fault detection and prediction in space habitats. This innovative approach leverages a digital twin simulation to accurately identify and predict system faults, minimizing false positives and enabling the discovery of hidden system behaviors!... show more
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4
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33
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Note: The citation metrics presented here have been sourced from Semantic Scholar and OpenAlex.

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