Learning from Failure [Extended Abstract]

被引：0

作者：

Grollman, Daniel H. ^{[1
]}

Billard, Aude G. ^{[1
]}

机构：

[1] Ecole Polytech Fed Lausanne, Learning Algorithms & Syst Lab, Lausanne, Switzerland

来源：

PROCEEDINGS OF THE 6TH ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTIONS (HRI 2011) | 2011年

关键词：

Learning from Demonstration;

D O I：

10.1145/1957656.1957703

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In the canonical Robot Learning from Demonstration scenario a robot observes performances of a task and then develops an autonomous controller. Current work acknowledges that humans may be suboptimal demonstrators and refines the controller for improved performance. However, there is still an assumption that the demonstrations are successful examples of the task. We here consider the possibility that the human has failed, and propose a model to minimize the possibility of the robot making the same mistakes.

引用

页码：145 / 146

页数：2

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