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How a Generative Encoding Fares as Problem-Regularity Decreases

  • Jeff Clune
  • Charles Ofria
  • Robert T. Pennock
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5199)

Abstract

It has been shown that generative representations, which allow the reuse of code, perform well on problems with high regularity (i.e. where a phenotypic motif must be repeated many times). To date, however, generative representations have not been tested on irregular problems. It is unknown how they will fare on problems with intermediate and low amounts of regularity. This paper compares a generative representation to a direct representation on problems that range from having multiple types of regularity to one that is completely irregular. As the regularity of the problem decreases, the performance of the generative representation degrades to, and then underperforms, the direct encoding. The degradation is not linear, however, yet tends to be consistent for different types of problem regularity. Furthermore, if the regularity of each type is sufficiently high, the generative encoding can simultaneously exploit different types of regularities.

Keywords

Evolution regularity modularity ANN NEAT HyperNEAT 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Jeff Clune
    • 1
  • Charles Ofria
    • 1
  • Robert T. Pennock
    • 1
    • 2
  1. 1.Department of Computer Science and EngineeringMichigan State UniversityEast LansingUSA
  2. 2.Department of Philosophy & Lyman Briggs CollegeMichigan State UniversityEast LansingUSA

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