arXiv cs.AI· Mark K. Ho, Michael L. Littman, James MacGlashan, Fiery Cushman, Joseph L. Austerweil·· 3 天前AI 评分22
展示与执行：通过演示进行教学
Showing versus Doing: Teaching by Demonstration
AI 导读
研究者提出一个贝叶斯模型来刻画"通过演示进行教学"，指出演示者有意教学（展示）与单纯执行任务（执行）时行为存在显著差异。两项人类实验表明，参与者的教学行为与模型预测一致，且标准 IRL 算法在从"展示"中学习时表现更优。
正文 · 原文
Abstract:People often learn from others' demonstrations, and inverse reinforcement learning (IRL) techniques have realized this capacity in machines. In contrast, teaching by demonstration has been less well studied computationally. Here, we develop a Bayesian model for teaching by demonstration. Stark differences arise when demonstrators are intentionally teaching (i.e. showing) a task versus simply performing (i.e. doing) a task. In two experiments, we show that human participants modify their teaching behavior consistent with the predictions of our model. Further, we show that even standard IRL algorithms benefit when learning from showing versus doing.
| Comments: | Published at NeurIPS 2016 (oral presentation). 12 pages, including supplementary materials |
| Subjects: | Machine Learning (cs.LG); Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC) |
| Cite as: | arXiv:2610.14004 [cs.LG] |
| (or arXiv:2610.14004v1 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2610.14004 arXiv-issued DOI via DataCite (pending registration) |
|
| Journal reference: | Advances in Neural Information Processing Systems 29 (NIPS 2016) |
Submission history
From: Mark Ho [view email]
[v1]
Sun, 27 Sep 2026 17:58:27 UTC (2,189 KB)
来源：arXiv cs.AI · arxiv.org