Deep Learning application to model learning in cognitive robotics

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Ariel Rodríguez-Jiménez
Esteban Arias-Méndez
Francisco Bellas-Bouza
Jose Becerra-Permuy

Abstract

The kind of training used for an artificial neural network will depend on factors such as: available data, training time, hardware resources, etc. The trainings can be online and offline. In the current article we experimented with online trainings on a robot whose main characteristic is the usage of a Cognitive Darwinist Mechanism to survive.


The robot learns in real-time. It has deep artificial neural networks to predict actions, it’s trained using the least amount of storage and the training time has to be as fast as possible; keeping high confidence in the artificial neural network.


The experimental trainings are: Online Deep Learning, Online Deep Learning with memory and Online Mini-Batch Deep Learning with memory.

Article Details

How to Cite
Rodríguez-Jiménez, A., Arias-Méndez, E., Bellas-Bouza, F., & Becerra-Permuy, J. (2020). Deep Learning application to model learning in cognitive robotics. Tecnología En Marcha Journal, 33(6), Pág. 92–104. https://doi.org/10.18845/tm.v33i6.5171
Section
Artículo científico