Abstract
Evolutionary Engineering (EE) challenge is to prove that it is possible to build systems (i.e. solutions) without going through any design process [3],[13]. Evolutionary Engineering is defined to be "the art of using evolutionary algorithms approach such as genetic algorithms [1] to build complex systems" [3]. Our main goal is to show that the EE-Method [6] is a good setting. In this paper we show step by step, using the EE-Method, how to build a neural net based system. The EE-Method can be viewed as just a GP appliance. The need of a well-specified approach determines the necessity for such method. Also, to improve the effectiveness of the evolvability principle on a complex systems, we present In this paper a more complex example than those in [7],[8]: an evolved neural net pattern recognizer that maps an input character image to a standard representation i.e. image or code.