让机器人用更懂用户的语言说明计划，理解更快。
Informative Communication of Robot Plans
- 基于用户心理模型设计信息量最大的说话顺序
- 实验表明理解目标速度比按序说明快得多
- 适合需要高效人机沟通的机器人应用
当机器人被要求口头说明其计划时，有多种表达方式。看似自然的增量式策略是按计划顺序逐条说明，但该策略忽略了用户已有的先验知识，导致信息传递效率低下。本文提出一种基于二阶心智理论（second-order theory of mind）的口语化策略，通过衡量每句话的信息增益来优化沟通顺序，使用户能更快速理解机器人的目标。实验结果显示，该方法在理解速度上显著优于按计划顺序或逆序说明等策略。此外，该框架还揭示了哪些信息具有价值及其原因，提升了沟通的可解释性。
原文摘要 · Abstract (English)
When a robot is asked to verbalize its plan it can do it in many ways. For example, a seemingly natural strategy is incremental, where the robot verbalizes its planned actions in plan order. However, an important aspect of this type of strategy is that it misses considerations on what is effectively informative to communicate, because not considering what the user knows prior to explanations. In this paper we propose a verbalization strategy to communicate robot plans informatively, by measuring the information gain that verbalizations have against a second-order theory of mind of the user capturing his prior knowledge on the robot. As shown in our experiments, this strategy allows to understand the robot's goal much quicker than by using strategies such as increasing or decreasing plan order. In addition, following our formulation we hint to what is informative and why when a robot communicates its plan.
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