Learning by demonstration with critique from a human teacher

Brenna Argall*, Brett Browning, Manuela Veloso

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

56 Scopus citations

Abstract

Learning by demonstration can be a powerful and natural tool for developing robot control policies. That is, instead of tedious hand-coding, a robot may learn a control policy by interacting with a teacher. In this work we present an algorithm for learning by demonstration in which the teacher operates in two phases. The teacher first demonstrates the task to the learner. The teacher next critiques learner performance of the task. This critique is used by the learner to update its control policy. In our implementation we utilize a 1-Nearest Neighbor technique which incorporates both training dataset and teacher critique. Since the teacher critiques performance only, they do not need to guess at an effective critique for the underlying algorithm. We argue that this method is particularly well-suited to human teachers, who are generally better at assigning credit to performances than to algorithms. We have applied this algorithm to the simulated task of a robot intercepting a ball. Our results demonstrate improved performance with teacher critiquing, where performance is measured by both execution success and efficiency.

Original languageEnglish (US)
Title of host publicationHRI 2007 - Proceedings of the 2007 ACM/IEEE Conference on Human-Robot Interaction - Robot as Team Member
Pages57-64
Number of pages8
DOIs
StatePublished - 2007
EventHRI 2007: 2007 ACM/IEEE Conference on Human-Robot Interaction - Robot as Team Member - Arlington, VA, United States
Duration: Mar 8 2007Mar 11 2007

Publication series

NameHRI 2007 - Proceedings of the 2007 ACM/IEEE Conference on Human-Robot Interaction - Robot as Team Member

Other

OtherHRI 2007: 2007 ACM/IEEE Conference on Human-Robot Interaction - Robot as Team Member
CountryUnited States
CityArlington, VA
Period3/8/073/11/07

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Software

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    Argall, B., Browning, B., & Veloso, M. (2007). Learning by demonstration with critique from a human teacher. In HRI 2007 - Proceedings of the 2007 ACM/IEEE Conference on Human-Robot Interaction - Robot as Team Member (pp. 57-64). (HRI 2007 - Proceedings of the 2007 ACM/IEEE Conference on Human-Robot Interaction - Robot as Team Member). https://doi.org/10.1145/1228716.1228725