Computational Complexity, Genetic Programming, and Implications

@inproceedings{Rylander2001ComputationalCG,
  title={Computational Complexity, Genetic Programming, and Implications},
  author={Bart Rylander and Terence Soule and James A. Foster},
  booktitle={EuroGP},
  year={2001}
}
Recent theory work has shown that a Genetic Program (GP) used to produce programs may have output that is bounded above by the GP itself [1]. This paper presents proofs that show that 1) a program that is the output of a GP or any inductive process has complexity that can be bounded by the Kolmogorov complexity of the originating program; 2) this result does not hold if the random number generator used in the evolution is a true random source; and 3) an optimization problem being solved with a… 

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