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. 2005 Feb-Apr;15(1-2):41-54.
doi: 10.1142/S0129065705000050.

Development of neural mechanisms for machine learning

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Development of neural mechanisms for machine learning

Artur M Arsenio. Int J Neural Syst. 2005 Feb-Apr.

Abstract

The goal of this work is to develop a humanoid robot's perceptual mechanisms through the use of learning aids. We describe methods to enable learning on a humanoid robot using learning aids such as books, drawing materials, boards, educational videos or other children toys. Visual properties of objects are learned and inserted into a recognition scheme, which is then applied to acquire new object representations - we propose learning through developmental stages. Inspired in infant development, we will also boost the robot's perceptual capabilities by having a human caregiver performing educational and play activities with the robot (such as drawing, painting or playing with a toy train on a railway). We describe original algorithms to extract meaningful percepts from such learning experiments. Experimental evaluation of the algorithms corroborates the theoretical framework.

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