Based on extensive experience in evolutionary optimization, both of chemical and electronic systems, including coevolutionary and spatially distributed techniques, we will find and optimize digital electronic control programs which enable the artificial electronic chemical cells to function and self-reproduce using online feedback from multicolor fluorescence microscopy. This program information will be associated with individual cells in the form of electronic genomes (see 5.3), and thereby serve as part of the evolvable genetic complement for the ECcells. For ICT applications, it is important to maintain information in dynamic systems with unreliable repair and information-copying. The interplay of chemical (scpDNA sequence) and electronic information can also be used to stabilize functional information associated with the ECCell cycle and its functionality and thus to stabilize this information on evolutionary timescales.
The evolutionary optimization of electrode control programs can take advantage of models of system behavior acquired through simulation of the physical and chemical processes (cf 5.2), making it possible to estimate suitable working points, starting algorithms and modules. We will develop an evolvable description for the electronic genomes in the space of possible image-electrode control programs. Populations of electrode control programs will reside in computer memory and be activated by downloading the information to active FPGA digital circuits that control the electrodes. The necessary technology for closing this loop is already in place and it will be used in this project.
