Genetic Programming was first introduced by Koza using tree representation together with a crossover technique in which random sub-branches of the parents' trees are swapped ...
Janet Clegg, James Alfred Walker, Julian Francis M...
This paper analyses the reliability of confidence intervals for Koza's computational effort statistic. First, we conclude that dependence between the observed minimum generat...
Although multi-objective GA (MOGA) is an efficient multiobjective optimization (MOO) method, it has some limitations that need to be tackled, which include unguaranteed uniformity...
Ken Harada, Jun Sakuma, Shigenobu Kobayashi, Isao ...
We have developed a technique to characterize software developers' styles using a set of source code metrics. This style fingerprint can be used to identify the likely author...
In this paper we describe a new class of representations for realvalued parameters called Center of Mass Encoding (CoME). CoME is based on variable length strings, it is self-adap...
Abstract. When researchers make alterations to the genetic programming algorithm they almost invariably wish to measure the change in performance of the evolutionary system. No one...
This work details an auction-based model for problem decomposition in Genetic Programming classification. The approach builds on the population-based methodology of Genetic Progra...
The conversion and extension of the Incremental Pareto-Coevolution Archive algorithm (IPCA) into the domain of Genetic Programming classification is presented. In particular, the ...
Abstract. We present EvA2, a comprehensive metaheuristic optimization framework with emphasis on Evolutionary Algorithms. It presents a modular structure of interfaces and abstract...