Reward Design For An Online Reinforcement Learning Algorithm Supporting Oral Self-Care.

ABSTRACT: While dental disease is largely preventable, professional advice on optimal oral hygiene practices is often forgotten or abandoned by patients. Therefore patients may benefit from timely and personalized encouragement to engage in oral self-care behaviors. In this paper, we develop an online reinforcement learning (RL) algorithm for use in optimizing the delivery of mobile-based prompts to encourage oral hygiene behaviors. One of the main challenges in developing such an algorithm is ensuring that the algorithm considers the impact of current actions on the effectiveness of future actions (i.e., delayed effects), especially when the algorithm has been designed to run stably and autonomously in a constrained, real-world setting characterized by highly noisy, sparse data. We address this cha

SUBMITTER: Trella AL 

PROVIDER: S-EPMC10457015 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature