Investigation of brood size in GP with brood recombination crossover for object recognition

  • Authors:

  • Mengjie Zhang;Xiaoying Gao;Weijun Lou;Dongping Qian

  • Affiliations:

  • School of Mathematics, Statistics and Computer Science, Victoria University of Wellington, Wellington, New Zealand and Artificial Intelligence Research Centre, Agricultural University of Hebei, Ba ...;School of Mathematics, Statistics and Computer Science, Victoria University of Wellington, Wellington, New Zealand and Artificial Intelligence Research Centre, Agricultural University of Hebei, Ba ...;School of Mathematics, Statistics and Computer Science, Victoria University of Wellington, Wellington, New Zealand;Artificial Intelligence Research Centre, Agricultural University of Hebei, Baoding, China

  • Venue:
  • PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
  • Year:
  • 2006

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Abstract

This paper describes an approach to the investigation of brood size in the brood recombination crossover method in genetic programming for object recognition problems. The approach is examined and compared with the standard crossover operator on three object classification problems of increasing difficulty. The results suggest that the brood recombination method outperforms the standard crossover operator for all the problems in terms of the classification accuracy. As the brood size increases, the system effective performance can be improved. When it exceeds a certain point, however, the effective performance will not be improved and the system will become less efficient.