A DRL-based event-triggered controller for networked artificial pancreas systems uses blood glucose change rules to formulate control as a semi-Markov decision process, improving communication efficiency.
Toward a Fully Automated Artificial Pancreas System Using a Bioinspired Reinforcement Learning Design: In Silico Vali- dation,
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Application of Deep Reinforcement Learning to Event-Triggered Control for Networked Artificial Pancreas Systems
A DRL-based event-triggered controller for networked artificial pancreas systems uses blood glucose change rules to formulate control as a semi-Markov decision process, improving communication efficiency.