In recent years, robotics has evolved, placing robots in social contexts, and giving rise to Human-Robot Interaction (HRI). HRI aims to improve user satisfaction by designing autonomous social robots with user modeling functionalities and user-adapted interactions, storing data on people to achieve personalized interactions. Personality, a vital factor in human interactions, influences temperament, social preferences, and cognitive abilities. Despite much research on personality traits influencing human-robot interactions, little attention has been paid to the influence of the robot's personality on the user model. Personality can influence not only temperament and how people interact with each other but also what they remember about an interaction or the person they interact with. A robot's personality traits could therefore influence what it remembers about the user and thus modify the user model and the consequent interactions. However, no studies investigating such conditioning have been found. This paper addresses this gap by proposing distinct user models that reflect unique robotic personalities, exploring the interplay between individual traits, memory, and social interactions to replicate human-like processes, providing users with more engaging and natural experiences

翻译：近年来，机器人技术不断发展，使机器人进入社交环境，并催生了人机交互（HRI）领域。HRI旨在通过设计具有用户建模功能和用户自适应交互能力的自主社交机器人，存储用户数据以实现个性化交互，从而提高用户满意度。个性作为人际互动中的关键因素，影响着人的气质、社交偏好和认知能力。尽管已有大量研究探讨个性特征对人机交互的影响，但机器人的个性对用户模型的影响却鲜受关注。个性不仅影响人的气质及人际互动方式，还会影响人们对互动内容或互动对象的记忆。因此，机器人的个性特征可能影响其对用户的记忆，从而改变用户模型及后续交互。然而，目前尚未发现对此类条件作用机制的研究。本文针对这一空白，提出反映独特机器人个性的差异化用户模型，通过探索个体特征、记忆与社交互动之间的相互作用来模拟类人认知过程，为用户提供更具吸引力和自然流畅的交互体验。