人間中心AIarXiv:2305.05607
サイド情報を活用した人間中心の自律性の洗練
Refining Human-Centered Autonomy Using Side Information
人間中心の自律システムにおいて、データ駆動型モデルに事前知識（サイド情報）を組み込むことで、安全性や正確性を向上させる方法を探る。
著者: Adam J. Thorpe
分類: cs.HC, cs.RO, cs.SY, eess.SY
原文アブストラクト
Data-driven algorithms for human-centered autonomy use observed data to compute models of human behavior in order to ensure safety, correctness, and to avoid potential errors that arise at runtime. However, such algorithms often neglect useful a priori knowledge, known as side information, that can improve the quality of data-driven models. We identify several key challenges in human-centered autonomy, and identify possible approaches to incorporate side information in data-driven models of human behavior.
