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Learning about objects with human teachers

Published: 09 March 2009 Publication History

Abstract

A general learning task for a robot in a new environment is to learn about objects and what actions/effects they afford. To approach this, we look at ways that a human partner can intuitively help the robot learn, Socially Guided Machine Learning. We present experiments conducted with our robot, Junior, and make six observations characterizing how people approached teaching about objects. We show that Junior successfully used transparency to mitigate errors. Finally, we present the impact of "social" versus "non-social" data sets when training SVM classifiers.

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cover image ACM Conferences
HRI '09: Proceedings of the 4th ACM/IEEE international conference on Human robot interaction
March 2009
348 pages
ISBN:9781605584041
DOI:10.1145/1514095
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 09 March 2009

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Author Tags

  1. interactive machine learning
  2. social robot learning

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HRI09
HRI09: International Conference on Human Robot Interaction
March 9 - 13, 2009
California, La Jolla, USA

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Overall Acceptance Rate 268 of 1,124 submissions, 24%

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ACM/IEEE International Conference on Human-Robot Interaction
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  • (2024)A Human-Centered View of Continual Learning: Understanding Interactions, Teaching Patterns, and Perceptions of Human Users Toward a Continual Learning Robot in Repeated InteractionsACM Transactions on Human-Robot Interaction10.1145/365911013:4(1-39)Online publication date: 23-Oct-2024
  • (2024)Interactive Continual Learning Architecture for Long-Term Personalization of Home Service Robots2024 IEEE International Conference on Robotics and Automation (ICRA)10.1109/ICRA57147.2024.10611386(11289-11296)Online publication date: 13-May-2024
  • (2024)Continuous and Interactive Language Learning and GroundingLifelong and Continual Learning Dialogue Systems10.1007/978-3-031-48189-5_4(77-101)Online publication date: 9-Jan-2024
  • (2023)Verbally Soliciting Human Feedback in Continuous Human-Robot CollaborationProceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction10.1145/3568162.3576980(290-300)Online publication date: 13-Mar-2023
  • (2023)Interactive Robot Learning: An OverviewHuman-Centered Artificial Intelligence10.1007/978-3-031-24349-3_9(140-172)Online publication date: 4-Apr-2023
  • (2022)Deep Learning Uncertainty in Machine TeachingProceedings of the 27th International Conference on Intelligent User Interfaces10.1145/3490099.3511117(173-190)Online publication date: 22-Mar-2022
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  • (2021)Perceptual and Semantic Processing in Cognitive RobotsElectronics10.3390/electronics1018221610:18(2216)Online publication date: 10-Sep-2021
  • (2021)Reinforcement Learning With Human Advice: A SurveyFrontiers in Robotics and AI10.3389/frobt.2021.5840758Online publication date: 1-Jun-2021
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