Estimation of Bayesian Network for Program Generation

@inproceedings{Hasegawa2006EstimationOB,
  title={Estimation of Bayesian Network for Program Generation},
  author={Yoshihiko Hasegawa and Hitoshi Iba},
  year={2006}
}
Genetic Programming (GP) is a powerful optimization algorithm, which employs crossover for a main genetic operator. Because a crossover operator in GP selects sub-trees randomly, the building blocks may be destroyed by crossover. Recently, algorithms called PMBGPs (Probabilistic Model Building GP) based on probabilistic techniques have been proposed in order to improve the problem above. We propose a new PMBGP employing Bayesian network for generating new individuals with a special chromosome… CONTINUE READING

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