Now I am working on the CTI project “MyTreat” at ARTORG Center. The scope of MyTreat is to develop a mobile platform for the personalized delivery of insulin for diabetic patients based on the combined use of reinforcement learning algorithms, a highly accurate patch pump, glucose monitoring devices and mobile phone technologies. The platform will be evaluated in both in silico and clinical environment. The diabetic patients, who are using insulin therapy, will benefit from our research outcome. More information regarding this project could also be found on the project website: www.mytreat.ch. Furthermore, you can also follow the twitter of our research group.

 

Characters of glucoregulatory system

Because of the following characters, the glucoregulatory system is difficult to control:

• Complex and non-linear
• Described by limited information
• Characterized by inter- and intra-patient variability
• Influenced by a number of factors e.g. meals, exercise (disturbances)
• Characterized by delays

 

Characters of reinforcement learning

Reinforcement learning (RL), branch of machine learning (ML), is an intensively active research field which embraces algorithms able to learn from data and perform optimization within uncertain environments. The field of RL falls between supervised and unsupervised learning and includes problems where an agent attempts to improve its performance over time at a given task through the continual interaction with its environment. RL began to develop as an independent branch in the early 1980s inspired by the animal psychology and the idea of learning through trial-and-error. It was quickly adopted by the field of optimal control as a very efficient way to solve dynamic programming problems for which the Bellman’s “curse of dimensionality” restricted an analytic solution. RL is a field with an extensively investigated theoretical background, which now finds its way towards practical application with the modern advancement in computational capacity. In this view, the application in real-life problems is being highlighted as one of the current trends of RL.