Learning from demonstration (LfD) is commonly considered to be a natural and intuitive way to allow novice users to teach motor skills to robots. However, it is important to acknowledge that the effectiveness of LfD is heavily dependent on the quality of teaching, something that may not be assured with novices. It remains an open question as to the most effective way of guiding demonstrators to produce informative demonstrations beyond ad hoc advice for specific teaching tasks. To this end, this paper investigates the use of machine teaching to derive an index for determining the quality of demonstrations and evaluates its use in guiding and training novices to become better teachers. Experiments with a simple learner robot suggest that guidance and training of teachers through the proposed approach can lead to up to 66.5% decrease in error in the learnt skill.
翻译:从演示(LfD)中学习通常被认为是一种自然和直觉的方式,使新用户能够向机器人传授运动技能;然而,重要的是,承认LfD的有效性在很大程度上取决于教学质量,这是用新手无法保证的;对于在特定教学任务特别建议之外如何最有效地指导示威者制作信息示范,这仍然是一个尚未解决的问题;为此,本文件调查了机器教学的使用,以得出确定演示质量的指数,并评估其在指导和培训新手以成为更好的教师方面的使用情况;与简单的学习机器人进行的实验表明,通过拟议方法指导和培训教师,可以导致学习技能错误减少66.5%。