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Limiting code growth to improve robustness in tree-based genetic programming

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GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation, 2, стр. 1763--1763. London, ACM Press, (7-11 July 2007)

Аннотация

In this paper we analyse the composition of the function set of the artificial ant problem to define new training and testing trails similar to the Santa Fe trail. Cross-validation is used in applications where large amounts of data are available. We also use a semantically driven growth limiter to reduce program size and check if growth reduction could lead to increased test performance.

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