信念・欲求・意図ロボットのための効果的な説明：いつ、何を説明するか
Effective Explanations for Belief-Desire-Intention Robots: When and What to Explain
キッチンでの掃除タスクを行うロボットを対象に、ユーザーが説明を求める状況と内容の好みを調査し、驚くような行動を特定して効果的な説明を生成する2つのアルゴリズムを提案した。
詳しい要約
1. どんなもの？
2. 先行研究と比べてどこがすごい？
3. 技術・手法の肝は？
4. どうやって有効だと検証した？
5. 議論はある？
6. 次に読むべき論文は？
※ AIが要旨から生成した要約です。正確性は原文をご確認ください。
著者: Cong Wang, Roberto Calandra, Verena Klös
分類: cs.RO, cs.AI
原文アブストラクト
When robots perform complex and context-dependent tasks in our daily lives, deviations from expectations can confuse users. Explanations of the robot's reasoning process can help users to understand the robot intentions. However, when to provide explanations and what they contain are important to avoid user annoyance. We have investigated user preferences for explanation demand and content for a robot that helps with daily cleaning tasks in a kitchen. Our results show that users want explanations in surprising situations and prefer concise explanations that clearly state the intention behind the confusing action and the contextual factors that were relevant to this decision. Based on these findings, we propose two algorithms to identify surprising actions and to construct effective explanations for Belief-Desire-Intention (BDI) robots. Our algorithms can be easily integrated in the BDI reasoning process and pave the way for better human-robot interaction with context- and user-specific explanations.
