User:Eugene M. Izhikevich/Proposed/NeuroEvolution of augmenting topologies (NEAT)

• Dr. Kenneth Stanley, University of Central Florida School of Electrical Engineering and Computer Science, FL

Dr. Kenneth Stanley accepted the invitation on 31 March 2008 (self-imposed deadline: 31 August 2008).

NeuroEvolution of augmenting topologies (NEAT) refers to an evolutionary algorithm designed to evolve artificial neural networks (ANNs) of increasing complexity over generations. ANNs can be evolved with NEAT for autonomous control, sequential decision making, game-playing, art, music, and other domains.

This article will be written over summer of 2008. It will provide motivation and details of the algorithm, as well as some of its history.