TY - DATA T1 - Data and code underlying the master thesis: Using Reinforcement Learning to Personalize Daily Step Goals for a Collaborative Dialogue with a Virtual Coach PY - 2023/10/02 AU - Martin Dierikx AU - Nele Albers AU - Willem-Paul Brinkman UR - DO - 10.4121/6f8e6750-7494-4226-b6f9-299a9edbb077.v1 KW - Virtual coach KW - Goal-setting KW - Physical activity KW - Behaviour change KW - Reinforcement learning KW - Personalization N2 -

This dataset contains the data and analysis code from the observational study conducted for the thesis: Using Reinforcement Learning to Personalize Daily Step Goals for a Collaborative Dialogue with a Virtual Coach. In this thesis, we studied the use of reinforcement learning to personalize daily step goal proposals based on people's personal factors, such as mood and self-motivation. To train the reinforcement learning model, we ran an observational study with a virtual coach to gather data on people's personal factors. We then ran analyses on simulations using the collected data to investigate the effectiveness of the model.

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