部分可观测环境中混合角色人类参与者的异步训练
Asynchronous Training of Mixed-Role Human Actors in a Partially-Observable Environment
AI总结：
本文提出了一种人类团队协作异步训练范式，通过自主队友替代人类进行训练，并引入了一种基于轨迹聚类简化实验的新颖设计，为未来利用机器人替代人类队友的协作异步训练系统提供了设计建议。
摘要：
在协作训练中，团队中的人类在复杂任务上进行协调，建立队友的心理模型，并学习实时适应队友的行动。为了减少协作训练通常带来的严苛的日程安排限制，本文引入了一种人类团队协作异步训练范式，在该范式中，受训者与自主队友而非人类进行协调练习。我们引入了一种新颖的实验设计，用于评估自主队友在协作训练中作为训练伙伴的表现。我们将该设计应用于一项人类受试者实验，在实验中，人类受训者与另一名人类或一名自主队友一起接受训练，并在一项为本研究所开发的全新的、部分可观测的协作游戏中与一名新的人类受试者一起接受评估。重要的是，我们采用了一种方法，对实验中表现出的演示中的队友轨迹进行聚类，以形成数量更少的训练条件。这简化了实验设计，使我们能够在合理的时间内开展一项复杂的协作训练人类受试者研究。通过对所提出的实验设计的演示，我们为未来利用机器人替代人类队友的协作异步训练系统的开发研究提供了要点和设计建议。
英文摘要：
In cooperative training, humans within a team coordinate on complex tasks, building mental models of their teammates and learning to adapt to teammates' actions in real-time. To reduce the often prohibitive scheduling constraints associated with cooperative training, this article introduces a paradigm for cooperative asynchronous training of human teams in which trainees practice coordination with autonomous teammates rather than humans. We introduce a novel experimental design for evaluating autonomous teammates for use as training partners in cooperative training. We apply the design to a human-subjects experiment where humans are trained with either another human or an autonomous teammate and are evaluated with a new human subject in a new, partially observable, cooperative game developed for this study. Importantly, we employ a method to cluster teammate trajectories from demonstrations performed in the experiment to form a smaller number of training conditions. This results in a simpler experiment design that enabled us to conduct a complex cooperative training human-subjects study in a reasonable amount of time. Through a demonstration of the proposed experimental design, we provide takeaways and design recommendations for future research in the development of cooperative asynchronous training systems utilizing robot surrogates for human teammates.
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。
