Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
The evolution of evolvability in genetic programming
Advances in genetic programming
Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
The royal tree problem, a benchmark for single and multiple population genetic programming
Advances in genetic programming
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Advances in genetic programming
Fitness Distance Correlation And Problem Difficulty For Genetic Programming
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
A comparison of linear genetic programming and neural networks inmedical data mining
IEEE Transactions on Evolutionary Computation
A tunable model for multi-objective, epistatic, rugged, and neutral fitness landscapes
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Size control with maximum homologous crossover
EA'05 Proceedings of the 7th international conference on Artificial Evolution
Geometric crossover for biological sequences
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
Operator equalisation for bloat free genetic programming and a survey of bloat control methods
Genetic Programming and Evolvable Machines
Parallel linear genetic programming for multi-class classification
Genetic Programming and Evolvable Machines
Robustness and evolvability of recombination in linear genetic programming
EuroGP'13 Proceedings of the 16th European conference on Genetic Programming
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We introduce a new recombination operator, the Maximum Homologous Crossover for Linear Genetic Programming. In contrast to standard crossover, it attempts to preserve similar structures from parents, by aligning them according to their homology, thanks to an algorithm used in Bio-Informatics. To highlight disruptive effects of crossover operators, we introduce the Royal Road landscapes and the Homology Driven Fitness problem, for Linear Genetic Programming. Two variants of the new crossover operator are described and tested on this landscapes. Results show a reduction in the bloat phenomenon and in the frequency of deleterious crossovers.