Model-free robust optimal feedback mechanisms of biological motor control

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

Abstract

This paper studies human sensorimotor learning and control using the stochastic robust adaptive dynamic programming (RADP) theory. The obtained result provides a unified framework that can take into account several recently discovered phenomena, including the active regulation of motor variability, the presence of suboptimal inference, and the model-free learning, and explains how these factors may promote the sensorimotor learning. We apply our learning framework to a model of sensorimotor system, and discover remarkable consistency with different experimental observations. Moreover, a novel feature of the RADP algorithm in our learning framework is that the knowledge of a stabilizing initial control policy is not needed. All these observations further confirm our hypothesis that RADP is a sound computational principle for sensorimotor control.

Original languageEnglish (US)
Title of host publicationProceedings of the 2016 12th World Congress on Intelligent Control and Automation, WCICA 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2029-2034
Number of pages6
Volume2016-September
ISBN (Electronic)9781467384148
DOIs
StatePublished - Sep 27 2016
Event12th World Congress on Intelligent Control and Automation, WCICA 2016 - Guilin, China
Duration: Jun 12 2016Jun 15 2016

Other

Other12th World Congress on Intelligent Control and Automation, WCICA 2016
CountryChina
CityGuilin
Period6/12/166/15/16

Fingerprint

Dynamic programming
Feedback
Programming theory
Acoustic waves

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Science Applications

Cite this

Bian, T., & Jiang, Z-P. (2016). Model-free robust optimal feedback mechanisms of biological motor control. In Proceedings of the 2016 12th World Congress on Intelligent Control and Automation, WCICA 2016 (Vol. 2016-September, pp. 2029-2034). [7578698] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WCICA.2016.7578698

Model-free robust optimal feedback mechanisms of biological motor control. / Bian, Tao; Jiang, Zhong-Ping.

Proceedings of the 2016 12th World Congress on Intelligent Control and Automation, WCICA 2016. Vol. 2016-September Institute of Electrical and Electronics Engineers Inc., 2016. p. 2029-2034 7578698.

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

Bian, T & Jiang, Z-P 2016, Model-free robust optimal feedback mechanisms of biological motor control. in Proceedings of the 2016 12th World Congress on Intelligent Control and Automation, WCICA 2016. vol. 2016-September, 7578698, Institute of Electrical and Electronics Engineers Inc., pp. 2029-2034, 12th World Congress on Intelligent Control and Automation, WCICA 2016, Guilin, China, 6/12/16. https://doi.org/10.1109/WCICA.2016.7578698
Bian T, Jiang Z-P. Model-free robust optimal feedback mechanisms of biological motor control. In Proceedings of the 2016 12th World Congress on Intelligent Control and Automation, WCICA 2016. Vol. 2016-September. Institute of Electrical and Electronics Engineers Inc. 2016. p. 2029-2034. 7578698 https://doi.org/10.1109/WCICA.2016.7578698
Bian, Tao ; Jiang, Zhong-Ping. / Model-free robust optimal feedback mechanisms of biological motor control. Proceedings of the 2016 12th World Congress on Intelligent Control and Automation, WCICA 2016. Vol. 2016-September Institute of Electrical and Electronics Engineers Inc., 2016. pp. 2029-2034
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