A Deep Deterministic Policy Gradient control algorithm for Automatic Insulin Delivery

Abstract

This study investigates the use of Reinforcement Learning (RL) to optimize insulin infusion in Automated Insulin Delivery (AID) systems. The Deep Deterministic Policy Gradient (DDPG) algorithm is evaluated as a potential control strategy and compared to Model Predictive Control (MPC) and PID controllers using a highly realistic in silico simulation model. Simulations for adult Type 1 Diabetes (T1D) patients demonstrate that the DDPG controller effectively reduces hypo- and hyperglycemic episodes and improves glucose stability.