Toward a self-organizing pre-symbolic neural model representing sensorimotor primitives

Junpei Zhong*, Angelo Cangelosi, Stefan Wermter

*この研究の対応する著者

研究成果: Article査読

18 被引用数 (Scopus)

抄録

The acquisition of symbolic and linguistic representations of sensorimotor behavior is a cognitive process performed by an agent when it is executing and/or observing own and others' actions. According to Piaget's theory of cognitive development, these representations develop during the sensorimotor stage and the pre-operational stage. We propose a model that relates the conceptualization of the higher-level information from visual stimuli to the development of ventral/dorsal visual streams. This model employs neural network architecture incorporating a predictive sensory module based on an RNNPB (Recurrent Neural Network with Parametric Biases) and a horizontal product model. We exemplify this model through a robot passively observing an object to learn its features and movements. During the learning process of observing sensorimotor primitives, i.e., observing a set of trajectories of arm movements and its oriented object features, the pre-symbolic representation is self-organized in the parametric units. These representational units act as bifurcation parameters, guiding the robot to recognize and predict various learned sensorimotor primitives. The pre-symbolic representation also accounts for the learning of sensorimotor primitives in a latent learning context.

本文言語English
論文番号22
ジャーナルFrontiers in Behavioral Neuroscience
8
FEB
DOI
出版ステータスPublished - 2014 2 4
外部発表はい

ASJC Scopus subject areas

  • 行動神経科学
  • 認知神経科学
  • 神経心理学および生理心理学

フィンガープリント

「Toward a self-organizing pre-symbolic neural model representing sensorimotor primitives」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル