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Evolving Neural Mechanisms for an Iterated Discrimination Task: A Robot Based Model

  • Elio Tuci
  • Christos Ampatzis
  • Marco Dorigo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3630)

Abstract

This paper is about the design of an artificial neural network to control an autonomous robot that is required to iteratively solve a discrimination task based on time-dependent structures. The “decision making” aspect demands the robot “to decide”, during a sequence of trials, whether or not the type of environment it encounters allows it to reach a light bulb located at the centre of a simulated world. Contrary to other similar studies, in this work the robot employs environmental structures to iteratively make its choice, without previous experience disrupting the functionality of its decision-making mechanisms.

Keywords

Discrimination Task Light Bulb Autonomous Robot Dark Zone Robot Controller 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Elio Tuci
    • 1
  • Christos Ampatzis
    • 1
  • Marco Dorigo
    • 1
  1. 1.IRIDIAUniversité Libre de BruxellesBruxellesBelgium

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