Investigating the Baldwin effect on Cartesian Genetic Programming efficiency

Cartesian genetic programming (CGP) has an unusual genotype representation which makes it more efficient than Genetic programming (GP) in digital circuit design problem. However, to the best of our knowledge, all methods used in evolutionary design of digital circuits deal with rugged, complex search space, which results in long running time to obtain successful evolution. Therefore, employing a method to guide evolution in these spaces can facilitate achieving more reasonable results. It has been claimed that a two-step evolutionary scenario caused by benefit and cost of learning called Baldwin effect can guide evolution in the biology and artificial life. Therefore, we have been motivated to examine this effect on CGP. We observe using this scenario the success rate and evolution time of CGP improves dramatically especially when size of chromosomes increases.