Foundations of Evolutionary Computing

  • Michael Zaus
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 27)


Evolutionary computing is a transdisciplinary research field that centers on the emulation or simulation of natural evolution processes which in turn might be used as tools for designing and implementing artificial systems which are capable of interacting with and adapting to changing task environments. Our motivation to enter into the field of evolutionary computing (EC) is based on formal and methodological grounds. Formally, because we are interested in the algorithmic compression of EC techniques, thereby focusing our interest on minimal difference machines, called autogenetic algorithms (AGAs). Methodologically, because EC offers new ways to multivariate search in complex features spaces. The present EC approach differs in many respects from currently traded EC techniques such as genetic algorithms ([HOL92]), evolution strategies ([REC94], [SCH95]), or evolution programs in general ([MIC92]), but the basic structure as displayed in figure 9.1 is maintained for reasons of comparability.


Cellular Automaton Binary Vector Binary Sequence Algorithmic Compression Evolutionary Computing 
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 1999

Authors and Affiliations

  • Michael Zaus
    • 1
  1. 1.Institute for Cognitive ScienceUniversity of OldenburgOldenburgGermany

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