Multiscale Dynamic Learning in Cognitive Robotics

  • Pilar Caamaño
  • Andrés Faíña
  • Francisco Bellas
  • Richard J. Duro
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7931)

Abstract

This paper is concerned with the dynamics of Cognitive Developmental Robotic architectures and how to produce structures that allow these types of architectures to deal with the different time scales a robot must cope with. The most important types of dynamics that occur in different time scales are defined and different mechanisms within a particular cognitive architecture, the Multilevel Darwinist Brain, are suggested to model each one of them. The paper also proposes a novel neuroevolutionary technique, called τ-NEAT, in order to capture processes based on precise temporal cues. This technique is analyzed when addressing dynamic environments in a real robotic test.

Keywords

Cognitive Robotics Dynamic Learning Neuroevolution NEAT Delay-Based ANN 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Pilar Caamaño
    • 1
  • Andrés Faíña
    • 1
  • Francisco Bellas
    • 1
  • Richard J. Duro
    • 1
  1. 1.Integrated Group for Engineering ResearchUniversidade da CoruñaFerrolSpain

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