Generation and adaptation of neural networks by evolutionary techniques (GANNET)

This paper describes the use of an evolutionary design system known as GANNET to synthesize the structure of neural networks. Initial results are presented for two benchmark problems: the exclusive-or and the two-spirals. A variety of performance criteria and design components are used and comparisons are drawn between the performance of genetic algorithms and other related techniques on these problems.