• DocumentCode
    1693709
  • Title

    Active Learning of Joint Attention

  • Author

    Doniec, Marek W. ; Sun, Ganghua ; Scassellati, Brian

  • Author_Institution
    Dept. of Comput. Sci., Yale Univ., New Haven, CT
  • fYear
    2006
  • Firstpage
    34
  • Lastpage
    39
  • Abstract
    Joint attention is the skill of attending to the same object another person is looking at. The acquisition of this skill is crucial in children for the development of many social and communicative abilities, and has been proposed as a critical social capability for interactive robots. Although recent attempts to model the acquisition of this skill on a robot have been moderately successful (Nagai et al., 2003; Triesch et al., 2006), they all assume that the robot remains passive during the learning process. Infants, on the other hand, have already acquired some rudimentary sensorimotor skills by the time they start to learn joint attention. We believe that these sensorimotor skills can jumpstart and considerably accelerate the learning of joint attention. In this paper we demonstrate on a humanoid robot how to use pointing and reaching to accelerate the learning of joint attention. We show that a robot can acquire this skill with a 95 % accuracy after a total of only 220 training samples compared to 85% accuracy after totals of 10,000+ samples in other approaches.
  • Keywords
    humanoid robots; knowledge acquisition; learning (artificial intelligence); active learning; humanoid robot; interactive robots; joint attention; sensorimotor skills; skill acquisition; social capability; Acceleration; Computer science; Fingers; Humanoid robots; Neural networks; Pediatrics; Robot sensing systems; Sun;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Humanoid Robots, 2006 6th IEEE-RAS International Conference on
  • Conference_Location
    Genova
  • Print_ISBN
    1-4244-0200-X
  • Electronic_ISBN
    1-4244-0200-X
  • Type

    conf

  • DOI
    10.1109/ICHR.2006.321360
  • Filename
    4115577