Data and code underlying the master thesis: Using Reinforcement Learning to Personalize Daily Step Goals for a Collaborative Dialogue with a Virtual Coach

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.

本数据集包含为某学位论文开展的观察性研究的全部数据与分析代码，该论文主题为：《利用强化学习（Reinforcement Learning）为虚拟教练协作对话场景定制个性化每日步数目标》。在该论文中，我们研究了基于用户个体因素（如情绪、自我动机）定制每日步数建议目标的强化学习应用方法。为训练该强化学习模型，我们通过虚拟教练开展观察性研究以采集用户个体因素相关数据；随后基于采集得到的数据开展模拟分析，以探究该模型的有效性。