Bridging evolving micro-controllers and evolving molecules
The evolution of micro-controllers and the evolution of reactive biochemical molecules have in common the properties associated with being control systems. Biological evolution is not really conceivable without an extensive control apparatus involving intensive information processing and information storage.
Hitherto it is not fully understood how natural evolution managed to maintain the information it acquired over time and to both adapt to and shape the environment at the same time. So far, many computer models can show stabilization of information and adaptation to given environmental conditions but none of these computer-models show ongoing increases in complexity. The solutions found are usually minimal, in the sense that programs are only just able to exist in the artificial environments. If the environment is too harsh, the programs simply do not survive. Evolution usually very soon gets trapped in fixed-points or simple limit cycles.
Though the experimental procedures are difficult, similar behavior was observed with the few biochemical experiments addressing increasing complexity. The approach taken here assumes that the dynamics of evolution does not depend on myriad properties of the basic elementary entities, but instead only on a few as yet unknown features of dynamic interaction. Extraction of these necessary features is the ultimate goal of this research.