  Patients with diabetes who are self-monitoring have to decide right before
each meal how much insulin they should take. A standard bolus advisor exists,
but has never actually been proven to be optimal in any sense. We challenged
this rule applying Reinforcement Learning techniques on data simulated with
T1DM, an FDA-approved simulator developed by Kovatchev et al. modeling the
gluco-insulin interaction. Results show that the optimal bolus rule is fairly
different from the standard bolus advisor, and if followed can actually avoid
hypoglycemia episodes.
