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Paper detail

Computational Complexity Results for Genetic Programming and the Sorting Problem

Genetic Programming (GP) has found various applications. Understanding this type of algorithm from a theoretical point of view is a challenging task. The first results on the computational complexity of GP have been obtained for problems with isolated program semantics. With this paper, we push forward the computational complexity analysis of GP on a problem with dependent program semantics. We study the well-known sorting problem in this context and analyze rigorously how GP can deal with different measures of sortedness.

preprint2011arXivOpen access
Markus WagnerFrank Neumann
Neural and Evolutionary Computing
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Markus WagnerFrank Neumann

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