FocusHUMAN-ROBOT INTERACTION

Robots for the people, by the people: Personalizing human-machine interaction

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Science Robotics  22 Aug 2018:
Vol. 3, Issue 21, eaat7451
DOI: 10.1126/scirobotics.aat7451

Article Information

vol. 3 no. 21

DOI: 
https://doi.org/10.1126/scirobotics.aat7451
Published By: 
Science Robotics
History: 
  • Received March 31, 2018
  • Accepted July 25, 2018
Copyright & Usage: 
Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works http://www.sciencemag.org/about/science-licenses-journal-article-reuseThis is an article distributed under the terms of the Science Journals Default License.

Author Information

  1. Caitlyn Clabaugh* and
  2. Maja Matarić
  1. Department of Computer Science, University of Southern California, 3710 McClintock Avenue, Los Angeles, CA 90089, USA.
  1. ↵*Corresponding author. Email: clabaugh{at}usc.edu

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Article usage: August 2018 to June 2019

AbstractFullPdf
Aug 201811397631
Sep 201812866151
Oct 20183762117
Nov 20181602116
Dec 20182692511
Jan 20192152719
Feb 2019871412
Mar 20191381820
Apr 20191442014
May 2019761513
Jun 201975105

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  • Robots for the people, by the people: Personalizing human-machine interaction

    By Caitlyn Clabaugh, Maja Matarić

    Science Robotics

    Multimodal, interactive, and multitask machine learning can personalize human-machine interaction to a broad diversity of individuals.

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