Graph Based Crossover - A Case Study with the Busy Beaver Problem
Francisco Baptista Pereira, Penousal Machado, Ernesto J. F. Costa, Amílcar Cardoso · 1999
The success of the application of evolutionary approaches depends, to a large extent, on problem representation and on the used genetic operators. In this paper we introduce a new graph based crossover operator and compare it with classical two-point crossover. The study was carried out using a theoretical hard problem known as Busy Beaver. This problem involves the search for the Turing Machine that produces the maximum number of ones when started on a blank tape. Experimental results show that, in this domain, the new graph-based operator provides a clear advantage over two-point crossover. 1 INTRODUCTION Genetic operators play a particular important role in Evolutionary Computation. The task of recombination operators is to promote the exchange of genetic material between individuals. Typically, the operators used depend on the problem being solved and on the chosen representation. When using linear representations the most common operators are single-point, two-point...