Indirect Encoding of Neural Networks for Scalable Go

  title={Indirect Encoding of Neural Networks for Scalable Go},
  author={Jason Gauci and Kenneth O. Stanley},
The game of Go has attracted much attention from the artificial intelligence community. A key feature of Go is that humans begin to learn on a small board, and then incrementally learn advanced strategies on larger boards. While some machine learning methods can also scale the board, they generally only focus on a subset of the board at one time. Neuroevolution algorithms particularly struggle with scalable Go because they are often directly encoded (i.e. a single gene maps to a single… CONTINUE READING
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