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Robotic model of the contribution of gesture to learning to count

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Abstract
In this paper a robotic to connectionist model of the contribution of gesture to learning to count is presented. By formulating a recurrent artificial neural network model of the phenomenon and assessing its performance without and with gesture it is demonstrated that the proprioceptive signal connected with gesture carries information which may be exploited when learning to count. The behaviour of the model is similar to that of human children in terms of the effect of gesture, and the size of the counted set, although the detailed patterns of errors made by the model and human children are different.
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SYSTEMS

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MLA
Rucinski, M, A Cangelosi, and Tony Belpaeme. “Robotic Model of the Contribution of Gesture to Learning to Count.” 2012 IEEE INTERNATIONAL CONFERENCE ON DEVELOPMENT AND LEARNING AND EPIGENETIC ROBOTICS (ICDL). NEW YORK: IEEE, 2012. Print.
APA
Rucinski, M., Cangelosi, A., & Belpaeme, T. (2012). Robotic model of the contribution of gesture to learning to count. 2012 IEEE INTERNATIONAL CONFERENCE ON DEVELOPMENT AND LEARNING AND EPIGENETIC ROBOTICS (ICDL). Presented at the IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL), NEW YORK: IEEE.
Chicago author-date
Rucinski, M, A Cangelosi, and Tony Belpaeme. 2012. “Robotic Model of the Contribution of Gesture to Learning to Count.” In 2012 IEEE INTERNATIONAL CONFERENCE ON DEVELOPMENT AND LEARNING AND EPIGENETIC ROBOTICS (ICDL). NEW YORK: IEEE.
Chicago author-date (all authors)
Rucinski, M, A Cangelosi, and Tony Belpaeme. 2012. “Robotic Model of the Contribution of Gesture to Learning to Count.” In 2012 IEEE INTERNATIONAL CONFERENCE ON DEVELOPMENT AND LEARNING AND EPIGENETIC ROBOTICS (ICDL). NEW YORK: IEEE.
Vancouver
1.
Rucinski M, Cangelosi A, Belpaeme T. Robotic model of the contribution of gesture to learning to count. 2012 IEEE INTERNATIONAL CONFERENCE ON DEVELOPMENT AND LEARNING AND EPIGENETIC ROBOTICS (ICDL). NEW YORK: IEEE; 2012.
IEEE
[1]
M. Rucinski, A. Cangelosi, and T. Belpaeme, “Robotic model of the contribution of gesture to learning to count,” in 2012 IEEE INTERNATIONAL CONFERENCE ON DEVELOPMENT AND LEARNING AND EPIGENETIC ROBOTICS (ICDL), San Diego, CA, 2012.
@inproceedings{8197768,
  abstract     = {In this paper a robotic to connectionist model of the contribution of gesture to learning to count is presented. By formulating a recurrent artificial neural network model of the phenomenon and assessing its performance without and with gesture it is demonstrated that the proprioceptive signal connected with gesture carries information which may be exploited when learning to count. The behaviour of the model is similar to that of human children in terms of the effect of gesture, and the size of the counted set, although the detailed patterns of errors made by the model and human children are different.},
  author       = {Rucinski, M and Cangelosi, A and Belpaeme, Tony},
  booktitle    = {2012 IEEE INTERNATIONAL CONFERENCE ON DEVELOPMENT AND LEARNING AND EPIGENETIC ROBOTICS (ICDL)},
  isbn         = {978-1-4673-4963-5},
  keywords     = {SYSTEMS},
  language     = {eng},
  location     = {San Diego, CA},
  pages        = {6},
  publisher    = {IEEE},
  title        = {Robotic model of the contribution of gesture to learning to count},
  year         = {2012},
}

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