Genetic algorithms with sharing for multimodal function optimization
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
ALPS: the age-layered population structure for reducing the problem of premature convergence
Proceedings of the 8th annual conference on Genetic and evolutionary computation
A sequential niche technique for multimodal function optimization
Evolutionary Computation
Speciation as automatic categorical modularization
IEEE Transactions on Evolutionary Computation
Fitness sharing and niching methods revisited
IEEE Transactions on Evolutionary Computation
Diversity in genetic programming: an analysis of measures and correlation with fitness
IEEE Transactions on Evolutionary Computation
Exploiting the path of least resistance in evolution
Proceedings of the 10th annual conference on Genetic and evolutionary computation
On Crossover Success Rate in Genetic Programming with Offspring Selection
EuroGP '09 Proceedings of the 12th European Conference on Genetic Programming
Computers and Operations Research
Sequential metamodelling with genetic programming and particle swarms
Winter Simulation Conference
Comparison of experimental designs for simulation-based symbolic regression of manufacturing systems
Computers and Industrial Engineering
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This paper demonstrates the ability of Hereditary Repulsion to perform well on a range of diverse problem domains. Furthermore, we show that HR is practically invulnerable to the effects to overfitting and does not suffer a loss of generalisation, even in the late stages of evolution. We trace the source of this high quality performance to a pleasingly simple constraint at the heart of the HR algorithm. We confirm its effectiveness by incorporating the constraint into one of the benchmark systems, observing substantial improvements in the quality of generalisation in the evolved population.