Corpus ID: 237635520

Evolutionary Generative Adversarial Networks based on New Fitness Function and Generic Crossover Operator

@article{Li2021EvolutionaryGA,
  title={Evolutionary Generative Adversarial Networks based on New Fitness Function and Generic Crossover Operator},
  author={Junjie Li and Jingyao Li and Wenbo Zhou and Shuai L{\"u}},
  journal={ArXiv},
  year={2021},
  volume={abs/2109.11078}
}
Evolutionary generative adversarial networks (EGAN) attempts to alleviate mode collapse and vanishing gradient that plague generative adversarial networks by introducing evolutionary computation. However, E-GAN lacks a reasonable evaluation mechanism, which limits its effect. Moreover, E-GAN only contains mutation operators in its evolutionary step, while ignoring crossover operators. The crossover operator generates more competitive individuals by combining the good traits of multiple… Expand

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