用机器教学训练新手，让其教机器人更准更快。
Using Machine Teaching to Boost Novices' Robot Teaching Skill
- 用机器教学算法指导新手学习如何教机器人。
- 训练后教机器人技能准确率提升78.83%。
- 新技能教学能力也提升63.69%，可迁移应用。
最新研究表明，用户（尤其是新手）通过演示学习（LfD）教机器人任务并不容易。本文提出一个利用机器教学（MT）算法训练新手成为更好机器人教师的框架，并验证该能力是否在训练期后仍保持，以及能否泛化到未参与训练的新技能。通过一项被试间实验，让新手教机器人简单运动技能。结果表明，接受训练的受试者在机器人习得技能的准确性上平均提升78.83%，在未包含于训练中的新技能教学上平均提升63.69%。
原文摘要 · Abstract (English)
Recent evidence has shown that, contrary to expectations, it is difficult for users, especially novices, to teach robots tasks through LfD. This paper introduces a framework that leverages MT algorithms to train novices to become better teachers of robots, and verifies whether such teaching ability is retained beyond the period of training and generalises such that novices teach robots more effectively, even for skills for which training has not been received. A between-subjects study is reported, in which novice teachers are asked to teach simple motor skills to a robot. The results demonstrate that subjects that receive training show average 78.83% improvement in teaching ability (as measured by accuracy of the skill learnt by the robot), and average 63.69% improvement in the teaching of new skills not included as part of the training.
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