Spatial Concept Learning: A Spiking Neural Network Implementation in Virtual and Physical Robots

被引：2

作者：

Cyr, Andre ^{[1
]}

Theriault, Frederic ^{[2
]}

机构：

[1] Univ Ottawa, Sch Psychol, Ottawa, ON, Canada

[2] Cegep Vieux Montreal, Dept Comp Sci, Montreal, PQ, Canada

来源：

COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE | 2019年 / 2019卷

关键词：

D O I：

10.1155/2019/8361369

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

This paper proposes an artificial spiking neural network (SNN) sustaining the cognitive abstract process of spatial concept learning, embedded in virtual and real robots. Based on an operant conditioning procedure, the robots learn the relationship of horizontal/vertical and left/right visual stimuli, regardless of their specific pattern composition or their location on the images. Tests with novel patterns and locations were successfully completed after the acquisition learning phase. Results show that the SNN can adapt its behavior in real time when the rewarding rule changes.

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页数：8

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