Publications

Bloat Control in Genetic Programming with a Histogram-based Accept-Reject Method

Marc-André Gardner, Christian Gagné and Marc Parizeau

Abstract - Recent bloat control methods such as dynamic depth limit (DynLimit) and Dynamic Operator Equalization (DynOpEq) aim at modifying the tree size distribution in a population of genetic programs. Although they are quite efficient for that purpose, these techniques have the disadvantage of evaluating the fitness of many bloated Genetic Programming (GP) trees, and then rejecting most of them, leading to an important waste of computational resources. We are proposing a method that makes a histogram-based model of current GP tree size distribution, and uses the so-called accept-reject method for generating a population with the desired target size distribution, in order to make a stochastic control of bloat in the course of the evolution. Experimental results show that the method is able to control bloat as well as other state-of-the-art methods, with minimal additionnal computational efforts compared to standard tree-based GP.

Bibtex:

@inproceedings{Gardner899,
author    = { Marc-André Gardner and Christian Gagné and Marc Parizeau },
title     = { Bloat Control in Genetic Programming with a Histogram-based Accept-Reject Method },
booktitle = { Companion proc. of Genetic and Evolutionary Computation Conference (GECCO 2011) },
pages     = { 187-188 },
year      = { 2011 },
month     = { July 12-16 },
location  = { Dublin, Ireland }
}

Last modification: 2011/07/28 by cgagne

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