[afabisch]

This reminds me a lot of the work on compressed neural network from Jan Koutnik and his colleagues. They don't evolve topology of a NN, but they learn weights of a neural network in some compressed space. That seems to be very similar to weight sharing.

Here are some related papers:

- original idea: http://people.idsia.ch/~tino/papers/koutnik.gecco10.pdf

- vision-based TORCS: http://repository.supsi.ch/4548/1/koutnik2013fdg.pdf

- backpropagation with compressed weights: http://www.informatik.uni-bremen.de/~afabisch/files/2013_NN_...

For example, in the case of the cart pole (without swing up) benchmark a simple linear controller with equal positive weights is required which can easily be encoded with this approach.

[hardmaru]

Hi,

Thanks for the references. The GECCO paper on compressed network search has been a big influence on previous projects I worked on, see:

https://news.ycombinator.com/item?id=16694153

https://news.ycombinator.com/item?id=14883694

it’s a small community!