In this paper, we introduce a novel conceptual model for a robot's behavioral adaptation in its long-term interaction with humans, integrating dynamic robot role adaptation with principles of flow experience from psychology. This conceptualization introduces a hierarchical interaction objective grounded in the flow experience, serving as the overarching adaptation goal for the robot. This objective intertwines both cognitive and affective sub-objectives and incorporates individual and group-level human factors. The dynamic role adaptation approach is a cornerstone of our model, highlighting the robot's ability to fluidly adapt its support roles - from leader to follower - with the aim of maintaining equilibrium between activity challenge and user skill, thereby fostering the user's optimal flow experiences. Moreover, this work delves into a comprehensive exploration of the limitations and potential applications of our proposed conceptualization. Our model places a particular emphasis on the multi-person HRI paradigm, a dimension of HRI that is both under-explored and challenging. In doing so, we aspire to extend the applicability and relevance of our conceptualization within the HRI field, contributing to the future development of adaptive social robots capable of sustaining long-term interactions with humans.

翻译：本文提出了一种新颖的概念模型，旨在实现机器人在与人类长期交互中的行为适应，该模型将动态机器人角色适应与心理学中的流体验原理相结合。这一概念化过程引入了基于流体验的分层交互目标，作为机器人的总体适应目标。该目标融合了认知与情感两个子目标，并纳入了个体及群体层面的人因因素。动态角色适应方法是本模型的核心，它突显了机器人灵活调整其支持角色（从领导者到追随者）的能力，以维持活动挑战与用户技能之间的平衡，从而促进用户获得最优流体验。此外，本文深入探讨了所提出概念化模型的局限性与潜在应用。我们的模型特别强调多人人机交互范式，这一人机交互维度目前研究尚不充分且具有挑战性。借此，我们希望扩展所提概念化模型在人机交互领域的适用性与相关性，为未来能够维持人类长期交互的自适应社交机器人的发展做出贡献。