対話型学習から共構築型タスク学習へ
From Interactive to Co-Constructive Task Learning
ロボットが非専門家ユーザーから日常的にタスクを学ぶため、親子の相互作用に見られる「共構築」プロセスに着目し、その研究課題を整理したレビュー論文。
著者: Anna-Lisa Vollmer, Daniel Leidner, Michael Beetz, Britta Wrede
分類: cs.RO, cs.AI
原文アブストラクト
Humans have developed the capability to teach relevant aspects of new or adapted tasks to a social peer with very few task demonstrations by making use of scaffolding strategies that leverage prior knowledge and importantly prior joint experience to yield a joint understanding and a joint execution of the required steps to solve the task. This process has been discovered and analyzed in parent-infant interaction and constitutes a ``co-construction'' as it allows both, the teacher and the learner, to jointly contribute to the task. We propose to focus research in robot interactive learning on this co-construction process to enable robots to learn from non-expert users in everyday situations. In the following, we will review current proposals for interactive task learning and discuss their main contributions with respect to the entailing interaction. We then discuss our notion of co-construction and summarize research insights from adult-child and human-robot interactions to elucidate its nature in more detail. From this overview we finally derive research desiderata that entail the dimensions architecture, representation, interaction and explainability.
