A Feature Selection Approach for Emulating the Structure of Mental Representations

  • Marko Tscherepanow
  • Marco Kortkamp
  • Sina Kühnel
  • Jonathan Helbach
  • Christoph Schütz
  • Thomas Schack
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7064)

Abstract

In order to develop artificial agents operating in complex ever-changing environments, advanced technical memory systems are required. At this juncture, two central questions are which information needs to be stored and how it is represented. On the other hand, cognitive psychology provides methods to measure the structure of mental representations in humans. But the nature and the characteristics of the underlying representations are largely unknown. We propose to use feature selection methods to determine adequate technical features for approximating the structure of mental representations found in humans. Although this approach does not allow for drawing conclusions transferable to humans, it constitutes an excellent basis for creating technical equivalents of mental representations.

Keywords

Feature selection Mental representations Memory 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Marko Tscherepanow
    • 1
    • 4
  • Marco Kortkamp
    • 1
  • Sina Kühnel
    • 2
    • 4
  • Jonathan Helbach
    • 1
  • Christoph Schütz
    • 3
    • 4
  • Thomas Schack
    • 3
    • 4
  1. 1.Applied Informatics, Faculty of TechnologyCenter of Excellence Bielefeld UniversityBielefeldGermany
  2. 2.Physiological Psychology, Faculty of Psychology and Sport SciencesCenter of Excellence Bielefeld UniversityBielefeldGermany
  3. 3.Neurocognition and Action, Faculty of Psychology and Sport SciencesCenter of Excellence Bielefeld UniversityBielefeldGermany
  4. 4.CITEC, Cognitive Interaction TechnologyCenter of Excellence Bielefeld UniversityBielefeldGermany

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