利用解释来缓解机器人对话失败
Utilising Explanations to Mitigate Robot Conversational Failures
AI总结：
本文从人机交互视角探讨如何利用机器人解释行为来应对对话失败，提出通过表达可理解性、能力不足和共同基础来缓解失败，并展望HRI与可解释性研究的交叉潜力。
摘要：
本文概述了来自人机交互（HRI）及相邻领域的机器人失败检测工作，将失败作为审视机器人解释行为的机会。由于人形机器人在2020年代初期仍然是实验性工具，与机器人的交互绝大多数发生在受控环境中，通常用于研究各种交互现象。这类交互缺乏真实世界和大规模实验，并且往往忽视日常用户的“不完美性”。机器人解释可以通过表达机器人的可理解性和能力不足，并在共同基础的视角下，用于应对和缓解失败。在本文中，我讨论了失败如何为交互式对话机器人中的解释提供机会，以及HRI与可解释性研究交叉领域的潜力所在。
英文摘要：
This paper presents an overview of robot failure detection work from HRI and adjacent fields using failures as an opportunity to examine robot explanation behaviours. As humanoid robots remain experimental tools in the early 2020s, interactions with robots are situated overwhelmingly in controlled environments, typically studying various interactional phenomena. Such interactions suffer from real-world and large-scale experimentation and tend to ignore the 'imperfectness' of the everyday user. Robot explanations can be used to approach and mitigate failures, by expressing robot legibility and incapability, and within the perspective of common-ground. In this paper, I discuss how failures present opportunities for explanations in interactive conversational robots and what the potentials are for the intersection of HRI and explainability research.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
