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Evolving Genes to Balance a Pole

  • Miguel Nicolau
  • Marc Schoenauer
  • Wolfgang Banzhaf
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6021)

Abstract

We discuss how to use a Genetic Regulatory Network as an evolutionary representation to solve a typical GP reinforcement problem, the pole balancing. The network is a modified version of an Artificial Regulatory Network proposed a few years ago, and the task could be solved only by finding a proper way of connecting inputs and outputs to the network. We show that the representation is able to generalize well over the problem domain, and discuss the performance of different models of this kind.

Keywords

Generalisation Test Promoter Site Genetic Regulatory Network Cart Model Extra Protein 
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 2010

Authors and Affiliations

  • Miguel Nicolau
    • 1
  • Marc Schoenauer
    • 1
  • Wolfgang Banzhaf
    • 2
  1. 1.INRIA Saclay - Île-de-FranceLRI- Université Paris-SudParisFrance
  2. 2.Memorial UniversityNewfoundlandCanada

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