Evolving Neural Networks through Augmenting Topologies

@article{Stanley2002EvolvingNN,
  title={Evolving Neural Networks through Augmenting Topologies},
  author={Kenneth O. Stanley and Risto Miikkulainen},
  journal={Evolutionary Computation},
  year={2002},
  volume={10},
  pages={99-127}
}
An important question in neuroevolution is how to gain an advantage from evolving neural network topologies along with weights. [] Key Result NEAT is also an important contribution to GAs because it shows how it is possible for evolution to both optimize and complexify solutions simultaneously, offering the possibility of evolving increasingly complex solutions over generations, and strengthening the analogy with biological evolution.

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...

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