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GE in Dynamic Environments

  • Ian Dempsey
  • Michael O’Neill
  • Anthony Brabazon
Part of the Studies in Computational Intelligence book series (SCI, volume 194)

Abstract

In the previous Chapter we highlighted the fact that very little research has been conducted into the area of Genetic Programming (GP) in dynamic environments. In this book we outline the foundations of research to date with Grammatical Evolution (GE) for these kinds of non-stationary environments. As described earlier, GE possesses a number of features that differentiate it significantly from GP and it is these features that present the most interesting avenues for exploration in relation to dynamic environments, more so than in their application to static problems.

In this chapter we start out by detailing in Section 4.1 the very first steps which we have taken with GE into the domain of non-stationary environments. Following this, in Section 4.2, we discuss the potential strengths of GE for the challenges presented by a dynamic world. Finally outline in Section 4.3 how we build the foundations upon which GE can be developed for application in these formidable environments.

Keywords

Genetic Programming Genetic Code Dynamic Environment Neutral Network Evolutionary Search 
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 2009

Authors and Affiliations

  • Ian Dempsey
    • Michael O’Neill
      • Anthony Brabazon

        There are no affiliations available

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