A large class of systems of biological and technological relevance can be described as analog networks, that is, collections of dynamic devices interconnected by links of varying strength. Some examples of analog networks are genetic regulatory networks, metabolic networks, neural networks, analog electronic circuits, and control systems. Analog networks are typically complex systems that include nonlinear feedback loops and possess temporal dynamics at different time scales. Both the synthesis and reverse engineering of analog networks are recognized as knowledge-intensive activities, for which few systematic techniques exist.
In this paper we will discuss the general relevance of the analog network concept and describe an
evolutionary approach to the automatic synthesis and the reverse engineering of analog networks. The proposed approach is called analog genetic encoding (AGE) and realizes an implicit genetic encoding of analog networks. AGE permits the evolution of human-competi...