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. © 2010 Springer-Verlag.
CITATION STYLE
Williams, P. L., & Beer, R. D. (2010). Information dynamics of evolved agents. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6226 LNAI, pp. 38–49). https://doi.org/10.1007/978-3-642-15193-4_4
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