AppGP: An alternative structural representation for GP

Nicholas Freitag McPhee, Nick Hopper

Research output: Contribution to conferencePaper

1 Scopus citations

Abstract

It has been shown that standard genetic programming using standard subtree crossover is prone to a form of structural convergence which makes it extremely difficult to make changes near the root, occasionally causing runs to become trapped in local maxima. Based on these structural limitations we propose a different tree representation, AppGP, which we hope will avoid this problem in some cases. In this paper, we describe this representation, and compare its performance to the performance of standard GP on a suite of test problems. We find that on all of the test problems, AppGP does no worse than standard GP, and in several it does considerably better, suggesting that the representation warrants further study.

Original languageEnglish (US)
Pages1377-1383
Number of pages7
DOIs
StatePublished - Jan 1 1999
Event1999 Congress on Evolutionary Computation, CEC 1999 - Washington, DC, United States
Duration: Jul 6 1999Jul 9 1999

Other

Other1999 Congress on Evolutionary Computation, CEC 1999
CountryUnited States
CityWashington, DC
Period7/6/997/9/99

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