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 size and shape
Advances in genetic programming
Size Fair and Homologous Tree Crossovers for Tree Genetic Programming
Genetic Programming and Evolvable Machines
What Makes a Problem GP-Hard? Analysis of a Tunably Difficult Problem in Genetic Programming
Genetic Programming and Evolvable Machines
EuroGP '98 Proceedings of the First European Workshop on Genetic Programming
General schema theory for genetic programming with subtree-swapping crossover: part I
Evolutionary Computation
Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence (Studies in Computational Intelligence)
Genotype representations in grammatical evolution
Applied Soft Computing
Journal of Computer and System Sciences
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
What makes a problem GP-hard? validating a hypothesis of structural causes
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Operator-Based distance for genetic programming: subtree crossover distance
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
Evolutionary operator self-adaptation with diverse operators
EuroGP'12 Proceedings of the 15th European conference on Genetic Programming
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Some Genetic Programming (GP) systems have fewer structural constraints than expression tree GP, permitting a wider range of operators. Using one such system, TAG3P, we compared the effects of such new operators with more standard ones on individual fitness, size and depth, comparing them on a number of symbolic regression and tree structuring problems. The operator effects were diverse, as the originators had claimed. The results confirm the overall primacy of crossover, but strongly suggest that new operators can usefully supplement, or even replace, subtree mutation. They give a better understanding of the features of each operator, and the contexts where it is likely to be useful. They illuminate the diverse effects of different operators, and provide justification for adaptive use of a range of operators.