Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Explicitly defined introns and destructive crossover in genetic programming
Advances in genetic programming
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Proceedings of the European Conference on Genetic Programming
A study in program response and the negative effects of introns in genetic programming
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
A comparison of linear genetic programming and neural networks inmedical data mining
IEEE Transactions on Evolutionary Computation
A survey and taxonomy of performance improvement of canonical genetic programming
Knowledge and Information Systems
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The result of the program encoded into a Genetic Programming(GP) tree is usually returned by the root of that tree. However, this is not a general strategy. In this paper we present and investigate a new variant where the best subtree is chosen to provide the solution of the problem. The other nodes (not belonging to the best subtree) are deleted. This will reduce the size of the chromosome in those cases where its best subtree is different from the entire tree. We have tested this strategy on a wide range of regression and classification problems. Numerical experiments have shown that the proposed approach can improve both the search speed and the quality of results.