[vanderZwan]

Thank you, saved it for later. Do you have any other links to offer?

[ofrancon]

A few links you can look at if you're interested in neuroevolution, from the same group of researchers:

Ken Stanley and Risto Miikkulainen original NEAT (NeuroEvolution of Augmenting Topologies) paper: http://nn.cs.utexas.edu/downloads/papers/stanley.ec02.pdf

Ken Stanley's novelty search page, and a link to his book, "Why Greatness Cannot Be Planned: The Myth of the Objective": http://eplex.cs.ucf.edu/noveltysearch/userspage/

Risto Miikkulainen's Evolving Deep Neural Networks paper: https://arxiv.org/abs/1703.00548

Ken Stanley & team's work at Uber, with links to some recent papers: https://eng.uber.com/deep-neuroevolution/

[yazr]

Are these evolutionary techniques considered more or less sample-efficient (and or cpu-efficient) compared to DL with GD ??

[ericjang]

Here's a recent survey / observational science paper by some prominent "neuroevolution" / A-Life researchers. https://arxiv.org/abs/1803.03453. I found this refreshing because it's rare that science papers talk about the debugging and experimental process and debugging journeys underlying this research.

[peterstoziek]

Unfortunately not in this domain.