I’ll add to your observation about them being complete solutions. Also, since the author thinks they’re like NN’s, we’ll do a direct comparison where members ar

I’ll add to your observation about them being complete solutions. Also, since the author thinks they’re like NN’s, we’ll do a direct comparison where members are a complete solution. Here’s an evolutionary algorithm: 1. A series of NN models with random weights. 2. A way to score how well each NN model works. 3. Iteratively mixing pieces of models with each other based on how well they scored. I didn’t see that in articles about deep learning at all. It was like they were totally, different things. They were so different that I looked into using both GA’s and simulated annealing for optimization of NN’s. I’d say that EA’s and NN-like methods are different and complementary.