Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Recombination, selection, and the genetic construction of computer programs
Recombination, selection, and the genetic construction of computer programs
On evolutionary exploration and exploitation
Fundamenta Informaticae
How to solve it: modern heuristics
How to solve it: modern heuristics
Soft computing: integrating evolutionary, neural, and fuzzy systems
Soft computing: integrating evolutionary, neural, and fuzzy systems
Biases in the Crossover Landscape
Proceedings of the 3rd International Conference on Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
A Mathematical Analysis of Tournament Selection
Proceedings of the 6th International Conference on Genetic Algorithms
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
An autonomous explore/exploit strategy
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
An analysis of constructive crossover and selection pressure in genetic programming
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Simulation and the Monte Carlo Method (Wiley Series in Probability and Statistics)
Simulation and the Monte Carlo Method (Wiley Series in Probability and Statistics)
Backward-chaining evolutionary algorithms
Artificial Intelligence
A less destructive, context-aware crossover operator for GP
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
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In order to drive Genetic Programming (GP) search towards an optimal situation, balancing selection pressure between the parent and offspring selection phases is an important aspect and very challenging. Our previous work showed that stochastic elements cannot be removed from both parent and offspring selections and suggested that maximising diversity in parents and minimising randomness in offspring could provide significantly good performance. This paper conducts additional carefully designed experiments to further investigate how diverse the parent should be if the offspring selection pressure is intensive. This paper shows that any attempt on adding more selection pressure to the parent selection can result in lower GP performance, and the higher the parent selection pressure, the worse the GP performance. The results confirm and strengthen the finding in our previous work.