用智能体替代真人，实现异步协作训练，提升效率。
Asynchronous Training of Mixed-Role Human Actors in a Partially-Observable Environment
- 用自主智能体代替真人搭档，实现异步协作训练。
- 通过轨迹聚类减少实验条件，缩短研究周期。
- 为未来机器人替代队友的训练系统提供设计参考。
在协作训练中，人类团队需在复杂任务中协调配合，建立对队友的心理模型并实时适应其行为。为降低协作训练常面临的调度难题，本文提出一种基于自主队友的异步协作训练范式，让受训者与自动化队友协作而非真人。研究设计了一种新实验方法，评估自主队友作为训练伙伴的适用性。在一项人机实验中，参与者分别与真人或自主队友训练，并在新任务中与新受试者协作，该任务为本研究专为评估开发的、部分可观测的协作游戏。关键创新在于，采用轨迹聚类技术从示范数据中提取少量典型训练条件，大幅简化实验设计，使复杂的人机协作训练研究可在合理时间内完成。通过实证展示，本文为未来利用机器人代理进行协作异步训练系统的设计提供了可复用的建议与实践指导。
原文摘要 · Abstract (English)
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.
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