Is common developmental genome a panacea towards more complex problems?

The potentiality of using a common developmental mapping to develop not a specific, but different classes of architectures (i.e., species), holding different structural and/or computational phenotypic properties is an active area of research in the field of bio-inspired systems. To be able to develop such species, there is a need to understand the governing properties and the constraints involved for their development. In this work we investigate the ability of common developmental genomes to evolve more than one specie (i.e., computational architecture), towards problems with increasing complexity. The architectures considered as different species were cellular automata and boolean networks and the problem studied was a simple financial market model over various architecture sizes. We considered problem instances of the same problem, each having a higher level of complexity, i.e., an instance with no state memory and with a previous memory of 1-, 2-, 5- and 10-state. The results show that the common developmental genome was able to find better results for certain cell architectures sizes.