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Artificial Evolution: A Continuing SAGA

  • Inman Harvey
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2217)

Abstract

I start with a basic tutorial on Artificial Evolution, and then show the simplest possible way of implementing this with the Microbial Genetic Algorithm. I then discuss some shortcomings in many of the basic assumptions of the orthodox Genetic Algorithm (GA) community, and give a rather different perspective. The basic principles of SAGA (Species Adaptation GAs) will be outlined, and the concept of Neutral Networks, pathways of level fitness through a fitness landscape will be introduced. A practical example will demonstrate the relevance of this.

Keywords

Genetic Algorithm Mutation Rate Local Optimum Neutral Network Evolutionary Robotic 
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 2001

Authors and Affiliations

  • Inman Harvey
    • 1
  1. 1.Centre for the Study of EvolutionCentre for Computational Neuroscience and Robotics, School of Cognitive and Computing Sciences, University of SussexBrightonUK

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