I read Koza's "Genetic Programming: On the Programming of Computers by Means of Natural Selection" back in 1993, and a lot of the holdups were that computers an

I read Koza's "Genetic Programming: On the Programming of Computers by Means of Natural Selection" back in 1993, and a lot of the holdups were that computers and memory just weren't as good as today to deal with large solution space trials. Also, dead ends due to the choice of starting functions to evolve. Today using TWEANNs and other methods (Topology and Weight Evolving Neural Networks) is really a good way to go. I still like the early examples in Koza GP where you give it a few functions to evolve a boolean function. I had started studying neural networks way back in the 80s and hit pay dirt with Mark Watson's 1991 "Common LISP Modules. Artificial Intelligence in the Era of Neural Networks and Chaos Theory", which threw me into NLP, Chaos, and ANNs.