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Visualisation and Classification with Artificial Life

  • Alfred Ultsch
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

Systems that possess the ability of emergence through self-organization are a particular promising approach to Data Mining. In this paper, we describe a novel approach to emerging self organizing systems: artificial life forms, called DataBots, simulated in a computer show collective behavioural patterns that correspond to structural features in a high dimensional input space. Movement strategies for DataBots have been found and tested on a real world data set. Important structural properties could be found and visualized by the collective organisation of the artificial life forms.

Keywords

Data Mining Artificial Life Movement Strategy Multivariate Time Series Movement Program 
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 2000

Authors and Affiliations

  • Alfred Ultsch
    • 1
  1. 1.Department of Computer SciencePhillips-University of MarburgMarburgGermany

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