将心智理论引入机器人交互，让机器解释行为背后的意图。
Theory of Mind for Explainable Human-Robot Interaction
- 把心智理论作为可解释AI的一种形式，让机器人理解人类心理状态。
- 提出用XAI评估框架验证机器人解释是否真实反映内部推理过程。
- 强调用户视角的解释需求，推动AI从系统中心转向以人为本。
在人机交互（HRI）中，心智理论（ToM）旨在作为机器人接口的用户友好型后端，使机器人能够推断并响应人类的心理状态。当集成到机器人中时，ToM可使其内部模型适应用户行为，提升行为的可解释性与可预测性。类似地，可解释人工智能（XAI）致力于使AI系统透明可理解，以促进人类有效理解和互动。由于ToM在HRI中的目标与XAI一致，本文主张将ToM视为一种XAI形式，并通过可解释性评估框架（VXAI）及其七个理想特性进行评估。本文指出，现有ToM应用在HRI中存在关键缺陷：极少评估解释是否真实对应机器人实际的内部推理过程。为解决此问题，本文提出将ToM融入XAI框架。通过在XAI中嵌入ToM原则，主张转变研究视角——当前的XAI多聚焦于系统自身，常缺乏以用户为中心的解释。引入ToM将推动关注重心转向用户的认知需求和视角。
原文摘要 · Abstract (English)
Within the context of human-robot interaction (HRI), Theory of Mind (ToM) is intended to serve as a user-friendly backend to the interface of robotic systems, enabling robots to infer and respond to human mental states. When integrated into robots, ToM allows them to adapt their internal models to users' behaviors, enhancing the interpretability and predictability of their actions. Similarly, Explainable Artificial Intelligence (XAI) aims to make AI systems transparent and interpretable, allowing humans to understand and interact with them effectively. Since ToM in HRI serves related purposes, we propose to consider ToM as a form of XAI and evaluate it through the eValuation XAI (VXAI) framework and its seven desiderata. This paper identifies a critical gap in the application of ToM within HRI, as existing methods rarely assess the extent to which explanations correspond to the robot's actual internal reasoning. To address this limitation, we propose to integrate ToM within XAI frameworks. By embedding ToM principles inside XAI, we argue for a shift in perspective, as current XAI research focuses predominantly on the AI system itself and often lacks user-centered explanations. Incorporating ToM would enable a change in focus, prioritizing the user's informational needs and perspective.
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