Journal article

DRAHOŠOVÁ Michaela, SEKANINA Lukáš and WIGLASZ Michal. Adaptive Fitness Predictors in Coevolutionary Cartesian Genetic Programming. Evolutionary Computation. 2019, vol. 99, no. 99, pp. 1-27. ISSN 1063-6560.
Publication language:english
Original title:Adaptive Fitness Predictors in Coevolutionary Cartesian Genetic Programming
Pages:1-27
Place:US
Year:2019
Journal:Evolutionary Computation, Vol. 99, No. 99, US
ISSN:1063-6560
DOI:10.1162/evco_a_00229
Keywords
Cartesian genetic programming, coevolutionary algorithms, fitness prediction, symbolic regression, evolutionary design, image processing.
Annotation
In genetic programming (GP), computer programs are often coevolved with training data subsets that are known as fitness predictors. In order to maximize performance of GP, it is important to find the most suitable parameters of coevolution, particularly the fitness predictor size. This is a very time consuming process as the predictor size depends on a given application and many experiments have to be performed to find its suitable size. A new method is proposed which enables us to automatically adapt the predictor and its size for a given problem and thus to reduce not only the time of evolution, but also the time needed to tune the evolutionary algorithm. The method was implemented in the context of Cartesian genetic programming and evaluated using five symbolic regression problems and three image filter design problems. In comparison with three different CGP implementations, the time required by CGP search was reduced while the quality of results remained unaffected.
BibTeX:
@ARTICLE{
   author = {Michaela Draho{\v{s}}ov{\'{a}} and
	Luk{\'{a}}{\v{s}} Sekanina and Michal Wiglasz},
   title = {Adaptive Fitness Predictors in Coevolutionary
	Cartesian Genetic Programming},
   pages = {1--27},
   journal = {Evolutionary Computation},
   volume = {99},
   number = {99},
   year = {2019},
   ISSN = {1063-6560},
   doi = {10.1162/evco_a_00229},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php.en.iso-8859-2?id=11206}
}

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