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Information Dynamics of Evolved Agents

  • Paul L. Williams
  • Randall D. Beer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6226)

Abstract

Information-theoretic techniques have received much recent attention as tools for the analysis of embodied agents. However, while techniques for quantifying static information structure are well-established, the application of information theory to the analysis of temporal behavior is still in its infancy. Here we formulate a novel information-theoretic approach for analyzing the dynamics of information flow in embodied systems. To demonstrate our approach, we apply it to analyze a previously evolved model of relational categorization. The results of this analysis demonstrate the unique strengths of our approach for exploring the detailed structure of information dynamics, and point towards a natural synergy between temporally-extended information theory and dynamical systems theory.

Keywords

Information Gain Information Dynamics Object Size Stimulus Feature Size Information 
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 2010

Authors and Affiliations

  • Paul L. Williams
    • 1
  • Randall D. Beer
    • 1
    • 2
  1. 1.Cognitive Science Program 
  2. 2.School of Informatics and ComputingIndiana UniversityBloomingtonUSA

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