Spatial Concept Learning: A Spiking Neural Network Implementation in Virtual and Physical Robots
Joint Authors
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-04-01
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Cyr, André& Thériault, Frédéric. 2019. Spatial Concept Learning: A Spiking Neural Network Implementation in Virtual and Physical Robots. Computational Intelligence and Neuroscience،Vol. 2019, no. 2019, pp.1-8.
https://search.emarefa.net/detail/BIM-1129614
Modern Language Association (MLA)
Cyr, André& Thériault, Frédéric. Spatial Concept Learning: A Spiking Neural Network Implementation in Virtual and Physical Robots. Computational Intelligence and Neuroscience No. 2019 (2019), pp.1-8.
https://search.emarefa.net/detail/BIM-1129614
American Medical Association (AMA)
Cyr, André& Thériault, Frédéric. Spatial Concept Learning: A Spiking Neural Network Implementation in Virtual and Physical Robots. Computational Intelligence and Neuroscience. 2019. Vol. 2019, no. 2019, pp.1-8.
https://search.emarefa.net/detail/BIM-1129614
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1129614