论文标题
个人和团队信任对机器人群行为的偏好
Individual and Team Trust Preferences for Robotic Swarm Behaviors
论文作者
论文摘要
可以使用人类的偏好分析人类与多代理机器人群之间的信任。这些偏好由个体表示为一系列群体行为之间的有序比较序列。个人的偏好图可以从此顺序形成。另外，群可能会映射到特征向量空间。我们制定了线性优化问题，以在特征空间中找到可信赖的行为。扩展到人类团队，我们使用稀疏的优化公式定义了一种新颖的独特性度量，从而从一组个人的成对偏好中聚集了相似的个体。还检查了匿名未标记的成对偏好的情况，以找到平均可信赖的行为和最小协方差绑定，从而提供了对组凝聚力的见解。进行了一项用户研究，结果表明具有相似信任概况的个人可以聚集以促进人类舒适的团队。
Trust between humans and multi-agent robotic swarms may be analyzed using human preferences. These preferences are expressed by an individual as a sequence of ordered comparisons between pairs of swarm behaviors. An individual's preference graph can be formed from this sequence. In addition, swarm behaviors may be mapped to a feature vector space. We formulate a linear optimization problem to locate a trusted behavior in the feature space. Extending to human teams, we define a novel distinctiveness metric using a sparse optimization formulation to cluster similar individuals from a collection of individuals' labeled pairwise preferences. The case of anonymized unlabeled pairwise preferences is also examined to find the average trusted behavior and minimum covariance bound, providing insights into group cohesion. A user study was conducted, with results suggesting that individuals with similar trust profiles can be clustered to facilitate human-swarm teaming.
