CentralNotice From Wikipedia, the free encyclopedia Jump to: navigation , search NeuroEvolution of Augmenting Topologies ( NEAT ) is a genetic algorithm for the generation of evolving artificial neural networks (a neuroevolution technique) developed by Ken Stanley in 2002 while at The University of Texas at Austin . It alters both the weighting parameters and structures of networks, attempting to find a balance between the fitness of evolved solutions and their diversity. It is based on applying three key techniques: tracking genes with history markers to allow crossover among topologies, applying speciation (the evolution of species) to preserve innovations, and developing topologies incrementally from simple initial structures ("complexifying"). 1 Performance 2 Complexification 3 Implementation 4 Extensions 4.1 rtNEAT 4.2 Phased pruning 4.3 HyperNEAT 4.4 ...