Analysis Code for Bachelor Thesis: Using Reinforcement Learning to Determine When to Provide Human Support in Quitting Smoking with a Virtual Coach

doi:10.4121/19dc8011-1bcb-4143-a373-08718055dc7c.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/19dc8011-1bcb-4143-a373-08718055dc7c
Datacite citation style:
Li, Shirley (2024): Analysis Code for Bachelor Thesis: Using Reinforcement Learning to Determine When to Provide Human Support in Quitting Smoking with a Virtual Coach. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/19dc8011-1bcb-4143-a373-08718055dc7c.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

This repository contains the analysis code for the bachelor thesis titled "Quitting Smoking with a Virtual Coach: Using Reinforcement Learning to Decide When to Provide Human Support" by Shirley Li. This study investigated the use of reinforcement learning to determine when to provide human support in quitting smoking with a virtual coach. The data that is used for this research was collected by a study that is explained in OSF: https://osf.io/78cnr. The data will also be published and linked to the OSF form.


The implementation of the virtual coach can be found here: https://doi.org/10.5281/zenodo.11102861

history
  • 2024-06-21 first online, published, posted
publisher
4TU.ResearchData
format
.py .md .ipynb .png .pdf .txt
funding
  • This work is part of the multidisciplinary research project Perfect Fit, which is supported by several funders organized by the Netherlands Organization for Scientific Research (NWO), program Commit2Data - Big Data & Health (project number 628.011.211). Besides NWO, the funders include the Netherlands Organisation for Health Research and Development (ZonMw), Hartstichting, the Ministry of Health, Welfare and Sport (VWS), Health Holland, and the Netherlands eScience Center.
organizations
TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science

DATA

files (2)