From personalized timely notification to healthy habit formation: A feasibility study of reinforcement learning approaches on synthetic data
[ 1 ] Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ P ] employee
2021
chapter in monograph / paper
english
- Fogg behaviour model
- reinforcement learning
- digital behaviour change intervention
EN Cancer patients may struggle with mental wellbeing issues such as distress and depression. As a part of the CAPABLE project, we aim to develop a digital behaviour-change intervention that helps them build positive health habits and improve their wellbeing. The main challenge to the evaluation of the system is the lack of access to real data prior to intervention start. Therefore, first, we created a simulator that mimics patient responses to activity suggestions based on Fogg’s behaviour model. Later we used supervised and reinforcement learning methods to learn the best time of sending the patient prompts. We found that the reinforcement learning methods learn quickly not to over-notify patients and find prompt policies that are more effective in facilitating users in performing target activity than a random notification strategy, but are less effective than adaptive supervised learning method trained to predict patient responsiveness.
7 - 18
CC BY (attribution alone)
publisher's website
final published version
at the time of publication
5