Spatial Concept Learning: A Spiking Neural Network Implementation in Virtual and Physical Robots.
Journal
Computational intelligence and neuroscience
ISSN: 1687-5273
Titre abrégé: Comput Intell Neurosci
Pays: United States
ID NLM: 101279357
Informations de publication
Date de publication:
2019
2019
Historique:
received:
21
09
2018
accepted:
11
03
2019
entrez:
9
5
2019
pubmed:
9
5
2019
medline:
30
8
2019
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 31065256
doi: 10.1155/2019/8361369
pmc: PMC6466944
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
8361369Références
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