用机器教学指导新手教机器人，让示范更高效。
Training People to Reward Robots
- 用机器教学引导新手，仅8次示范就提升教学能力。
- 机器人学习性能提升89%，未见技能也提高70%。
- 适合想提升人机协作教学效率的研究者。
从示范学习（LfD）允许专家教师向机器人系统传授任务技能。然而，如何量化地指导新手教师达到专家水平的示范仍是一个开放问题。本文研究了机器教学（MT）在强化学习从示范（RLfD）中引导新手教师改进教学技能的作用。实验表明，接受MT指导的新手仅用8次示范即可训练机器人掌握特定运动技能，并泛化到未见过的技能。结果显示，MT指导使机器人在训练技能上的学习性能提升89%，在未见技能上的学习性能提升70%。这些发现表明MT指导能有效提升人类教学行为，从而改善RLfD中的示范质量。
原文摘要 · Abstract (English)
Learning from demonstration (LfD) is a technique that allows expert teachers to teach task-oriented skills to robotic systems. However, the most effective way of guiding novice teachers to approach expert-level demonstrations quantitatively for specific teaching tasks remains an open question. To this end, this paper investigates the use of machine teaching (MT) to guide novice teachers to improve their teaching skills based on reinforcement learning from demonstration (RLfD). The paper reports an experiment in which novices receive MT-derived guidance to train their ability to teach a given motor skill with only 8 demonstrations and generalise this to previously unseen ones. Results indicate that the MT-guidance not only enhances robot learning performance by 89% on the training skill but also causes a 70% improvement in robot learning performance on skills not seen by subjects during training. These findings highlight the effectiveness of MT-guidance in upskilling human teaching behaviours, ultimately improving demonstration quality in RLfD.
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