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原文
arXiv · Human-Computer Interaction· Chengwen Zhang, Jianyang Wang, Chang Liu, Yukun Wang, Yuan Xu, Zhoutong Ye, Jie Cai, Chun Yu, Yuanchun Shi·· 9 小时前AI 评分54

通过联合行动理解人机协作

Understanding Human-Robot Collaboration through Joint Action

AI 导读

联合行动理论为理解人机协作中的协调提供了概念,但这些概念在实证研究中如何落地仍较分散。作者按 PRISMA 2020 流程筛选出 2021 至 2026 年发表的 83 篇实证论文,用理论驱动的框架分析把文献组织为表征、预测与整合三种能力下的九个构念,并考察各构念在研究间的分布与共现,指出证据集中与缺失之处。原文为预印本,尚未经同行评审。

摘要

arXiv:2610.37298v1 Announce Type: new Abstract: Human-robot collaboration requires partners to coordinate interdependent contributions toward a shared goal. Joint Action theory provides concepts for understanding this coordination, but how these concepts are instantiated and combined across empirical research remains fragmented. We conducted a systematic review following PRISMA 2020, identifying 83 empirical papers published between 2021 and 2026. Through theory-driven framework analysis, we organized the literature into nine constructs across three capacities: Representation, Prediction, and Integration. We analyze how these constructs are distributed and co-occur across studies, revealing where empirical evidence concentrates and where it is absent. By mapping empirical HRC research onto a unified Joint Action framework, this review offers a coherent overview of HRC studies, identifies gaps in current evidence, and provides guidelines for future research.

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来源:arXiv · Human-Computer Interaction · arxiv.org

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