On the theory of designing circuits using genetic programming and a minimum of domain knowledge
The problem of analog circuit design is a difficult problem that is generally viewed as requiring human intelligence to solve. Considerable progress has been made in automating the design of certain categories of purely digital circuits; however, the design of analog electrical circuits and mixed analog-digital circuits has not proved to be as amenable to automation. When critical analog circuits are required for a project, skilled and highly trained experts are necessary. Previous work on applying genetic programming to the design of analog circuits has proved to be successful at evolving a wide variety of circuits, including filters, amplifiers and computational circuits; however, these previous approaches have required the specification of an appropriate embryonic circuit. This paper explores a method to eliminate even this small amount of problem-specific knowledge, and, in addition, proves that the representation used is capable of producing all circuits.