TIP: A Trust Inference and Propagation Model in Multi-Human Multi-Robot Teams
TIP: A Trust Inference and Propagation Model in Multi-Human Multi-Robot Teams
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DOI：
10.1145/3568294.3580164
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发表时间：
2023-01
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影响因子：
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通讯作者：
Yaohui Guo;Jessie X. Yang;Cong Shi
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文献类型：
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作者：
Yaohui Guo;Jessie X. Yang;Cong Shi
信任已被确定为有效的人机合作的核心因素。现有的文献信任建模主要集中在二元人类自治团队，其中一个人类代理与一个机器人进行交互。有很少，如果不是没有，在由多个人类代理和多个机器人代理组成的团队中的信任建模的研究。为了填补这一研究空白，我们提出了信任推理和传播（TIP）模型的信任建模在多人多机器人团队。我们断言，在一个多人多机器人团队中，存在两种类型的经验，任何人类代理与任何机器人：直接和间接的经验。TIP模型提出了一个新的数学框架，明确说明了这两种类型的经验。为了评估该模型，我们进行了一项人类受试者实验，有15对参与者（N=30）。每对都用两架无人机执行搜索和探测任务。结果表明，我们的TIP模型成功地捕捉到了潜在的信任动态，并显着优于基线模型。据我们所知，TIP模型是多人多机器人团队中计算信任建模的第一个数学框架。
Trust has been identified as a central factor for effective human-robot teaming. Existing literature on trust modeling predominantly focuses on dyadic human-autonomy teams where one human agent interacts with one robot. There is little, if not no, research on trust modeling in teams consisting of multiple human agents and multiple robotic agents. To fill this research gap, we present the trust inference and propagation (TIP) model for trust modeling in multi-human multi-robot teams. We assert that in a multi-human multi-robot team, there exist two types of experiences that any human agent has with any robot: direct and indirect experiences. The TIP model presents a novel mathematical framework that explicitly accounts for both types of experiences. To evaluate the model, we conducted a human-subject experiment with 15 pairs of participants (N=30). Each pair performed a search and detection task with two drones. Results show that our TIP model successfully captured the underlying trust dynamics and significantly outperformed a baseline model. To the best of our knowledge, the TIP model is the first mathematical framework for computational trust modeling in multi-human multi-robot teams.