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 royal tree problem, a benchmark for single and multiple population genetic programming
Advances in genetic programming
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Fitness Distance Correlation as a Measure of Problem Difficulty for Genetic Algorithms
Proceedings of the 6th International Conference on Genetic Algorithms
Maintaining the Diversity of Genetic Programs
EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
General schema theory for genetic programming with subtree-swapping crossover: part I
Evolutionary Computation
Problem Difficulty and Code Growth in Genetic Programming
Genetic Programming and Evolvable Machines
A Study of Fitness Distance Correlation as a Difficulty Measure in Genetic Programming
Evolutionary Computation
Fitness distance correlation in structural mutation genetic programming
EuroGP'03 Proceedings of the 6th European conference on Genetic programming
Operator-Based distance for genetic programming: subtree crossover distance
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
Diversity in genetic programming: an analysis of measures and correlation with fitness
IEEE Transactions on Evolutionary Computation
Using crossover based similarity measure to improve genetic programming generalization ability
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Fitness landscapes and problem hardness in genetic programming
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Definition of a crossover based distance for genetic algorithms
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Fitness landscapes and problem hardness in genetic programming
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Theoretical results in genetic programming: the next ten years?
Genetic Programming and Evolvable Machines
Open issues in genetic programming
Genetic Programming and Evolvable Machines
A study of the neutrality of Boolean function landscapes in genetic programming
Theoretical Computer Science
An empirical approach to the measurement of interchromosomal distances in the genetic algorithm
Proceedings of the 14th annual conference on Genetic and evolutionary computation
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To analyse various properties of the search process of genetic programming it is useful to quantify the distance between two individuals. Using operator-based distance measures can make this analysis more accurate and reliable than using distance measures which have no relationship with the genetic operators. This paper extends a recent definition of a distance measure based on subtree crossover for genetic programming. Empirical studies are presented that show the suitability of this measure to dynamically calculate the fitness distance correlation coefficient during the evolution, to construct a fitness sharing system for genetic programming and to measure genotypic diversity in the population. These experiments confirm the accuracy of the new measure and its consistency with the subtree crossover genetic operator.