论文标题
从外观来看：机器人凝视策略对人类合作的影响
Judging by the Look: The Impact of Robot Gaze Strategies on Human Cooperation
论文作者
论文摘要
人眼目光在传递信息，交流意图和理解他人的心理状态方面起着重要作用。先前的研究表明，机器人的目光也会影响人类在互动过程中的决策和策略。然而，有限的研究已经在人类机器人相互作用方案中训练了针对基于凝视数据的人形机器人。考虑到凝视会影响社会交流的自然性并改变了观察者的决策过程，应将其视为人类机器人互动中的关键组成部分。为了研究机器人凝视对人类的影响，我们提出了一种体现的神经模型，用于进行类似人类的视线转移。这是通过扩展社会关注模型并在吸引人的数据上训练它来实现的，该数据通过观看人类玩游戏而收集。我们将比较在人类合作游戏中采用不同凝视策略的机器人面前的人类行为表现。
Human eye gaze plays an important role in delivering information, communicating intent, and understanding others' mental states. Previous research shows that a robot's gaze can also affect humans' decision-making and strategy during an interaction. However, limited studies have trained humanoid robots on gaze-based data in human-robot interaction scenarios. Considering gaze impacts the naturalness of social exchanges and alters the decision process of an observer, it should be regarded as a crucial component in human-robot interaction. To investigate the impact of robot gaze on humans, we propose an embodied neural model for performing human-like gaze shifts. This is achieved by extending a social attention model and training it on eye-tracking data, collected by watching humans playing a game. We will compare human behavioral performances in the presence of a robot adopting different gaze strategies in a human-human cooperation game.
