pavelchristof

3 ms·

1. 1.▲
   by pavelchristof 9y ago

   Saddle points are not much of an issue too: https://arxiv.org/abs/1710.07406
2. 2.▲
   by pavelchristof 9y ago

   The fact that you don't need your fitness function to be differentiable is a big advantage :) if you had the gradient it would always help to use it. In reinforcement learning: evolutionary algorithms work by applying peturbations in t
3. 3.▲
   by pavelchristof 9y ago

   Absolutely no. Random search does not work in high dimensions because of the "curse of dimensionality" - the number of directions to search grows exponentially with dimension. Gradient descent avoids the problem because it knows t