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Robot competence development by constructive learning

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posted on 18.09.2017 by Qinggang Meng, Mark H. Lee, Christopher Hinde
This paper presents a constructive learning approach for developing sensor-motor mapping in autonomous systems. The system's adaptation to environment changes is discussed and three methods are proposed to deal with long term and short term changes. The proposed constructive learning allows autonomous systems to develop network topology and adjust network parameters. The approach is supported by findings from psychology and neuroscience especially during infants cognitive development at early stages. A growing radial basis function network is introduced as a computational substrate for sensory-motor mapping learning. Experiments are conducted on a robot eye/hand coordination testbed and results show the incremental development of sensory-motor mapping and its adaptation to changes such as in tool-use.

History

School

  • Science

Department

  • Computer Science

Published in

Lecture Notes in Electrical Engineering

Volume

48 LNEE

Pages

15 - 26

Citation

MENG, Q., LEE, M. and HINDE, C., 2010. Robot competence development by constructive learning. IN: Ao, S. ... et al. (eds.). Advances in Machine Learning and Data Analysis. (Lecture Notes in Electrical Engineering ; 48.) London: Springer, pp.15-26.

Publisher

© Springer

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2010

Notes

The final publication is available at Springer via: https://doi.org/10.1007/978-90-481-3177-8_2.

ISBN

9789048131778;9048131774;9789048131761;9048131766

ISSN

1876-1100

eISSN

1876-1119

Book series

Lecture Notes in Electrical Engineering;48

Language

en

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