Neuroevolution: Evolving Novel Neural Network Architectures with Kenneth Stanley - TWiML Talk #94

This article discusses neuroevolution, a method of evolving neural network architectures using genetic algorithms. It features an interview with Kenneth Stanley, a leading researcher in this field. The conversation covers Stanley's work, including the Neuroevolution of Augmenting Topologies (NEAT) paper, HyperNEAT, and novelty search. The article highlights the potential of neuroevolution to create more complex and human-like neural networks, as well as approaches that prioritize novel behaviors over predefined objectives. The discussion also touches upon the relationship between biology and computation, and Stanley's other projects.