Corpus ID: 14344233

The Fundamental Learning Problem that Genetic Algorithms with Uniform Crossover Solve Efficiently and Repeatedly As Evolution Proceeds

@article{Burjorjee2013TheFL,
  title={The Fundamental Learning Problem that Genetic Algorithms with Uniform Crossover Solve Efficiently and Repeatedly As Evolution Proceeds},
  author={Keki M. Burjorjee},
  journal={ArXiv},
  year={2013},
  volume={abs/1307.3824}
}
  • Keki M. Burjorjee
  • Published 2013
  • Computer Science
  • ArXiv
  • This paper establishes theoretical bonafides for implicit concurrent multivariate effect evaluation--implicit concurrency for short---a broad and versatile computational learning efficiency thought to underlie general-purpose, non-local, noise-tolerant optimization in genetic algorithms with uniform crossover (UGAs). We demonstrate that implicit concurrency is indeed a form of efficient learning by showing that it can be used to obtain close-to-optimal bounds on the time and queries required to… CONTINUE READING

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