评估HTN（A-HTN）用于3D严肃游戏中的自动任务性能评估
Assessment HTN (A-HTN) for Automated Task Performance Assessment in 3D Serious Games
摘要：
近年来，各种3D混合现实严肃游戏已经被开发用于不同的应用，诸如体育训练、康复和教育。在一个严肃的游戏中，任务表现是衡量用户如何有效和准确地完成游戏目标的指标。先前的研究包括基于图形的任务表示，例如分层任务网络（HTN），它只对游戏的任务进行建模，但不进行评估。在本文中，我们提出了评估HTN（A-HTN），它既有效地建模任务，并结合评估逻辑的游戏目标。基于如何评估任务性能，A-HTN自动执行：（a）通过比较对象操作的任务级评估和（b）通过比较运动轨迹的运动级评估。系统还可以基于谁正在被评估而将任务表现评估分类为单用户或多用户。我们使用两个3D VR严肃游戏来展示A-HTN的有效性：一个液体比重计实验和一个多用户化学实验。的A-HTN实验表明，教师的分数和系统生成的分数之间的高度相关性，表明建议的A-HTN推广自动评估与主题专家。
英文摘要：
In the recent years, various 3D mixed reality serious games have been developed for different applications such as physical training, rehabilitation, and education. Task performance in a serious game is a measurement of how efficiently and accurately users accomplish the game's objectives. Prior research includes a graph-based representation of tasks, e.g. Hierarchical Task Network (HTN), which only models a game's tasks but does not perform assessment. In this paper, we propose Assessment HTN (A-HTN), which both models the task efficiently and incorporates assessment logic for game objectives. Based on how the task performance is evaluated, A-HTN automatically performs: (a) Task-level Assessment by comparing object manipulations and (b) Action-level Assessment by comparing motion trajectories. The system can also categorize the task performance assessment into single user or multi-user based on who is being assessed. We showcase the effectiveness of the A-HTN using two 3D VR serious games: a hydrometer experiment and a multi-user chemistry experiment. The A-HTN experiments show a high correlation between instructor scores and the system generated scores indicating that the proposed A-HTN generalizes automatic assessment at par with Subject Matter Experts.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
