Multi-cellular Reconfigurable Circuits: Evolution, Morphogenesis and Learning

Bio-inspired electronic circuits have the potential to address some of the shortcomings of conventional electronic circuits, such as lack of applicability to ill-defined problems, of robustness, or of adaptivity to unexpectedly changing environments. Bio-inspired circuits are designed by taking inspiration from principles observed in biology. The evolution of biological organisms, their development from a fertilized egg, and their learning capabilities are three sources of bio-inspiration that can be used for this purpose. Until now bio-inspired electronics mostly focused on a single aspect of bio-inspiration: either evolution, development or learning. In this thesis we consider that electronic circuits should encompass all three aspects to fully benefit from bio-inspiration. These circuits capable of evolution, development and learning are called POEtic circuits (POE stands for phylogeny, ontogeny and epigenesis, that mean respectively evolution, development and learning). Conceptually these POEtic circuits, much like biological organisms, are multi-cellular circuits that evolve following the principles of selection and differential reproduction, they develop from a single cell and differentiate according to inter-cellular and environmental signals, and eventually they learn during their lifetime. These circuits may also dynamically reorganize their structure in order to cope with changes in the environment, or when they are expanded with new cells, sensors or actuators. In comparison to conventional circuits, POEtic circuits are created automatically using evolutionary principles, even if only a partial or high-level specification of the problem is known. Development provides a complex genotype to phenotype mapping, that may lead to fault-tolerance or adaptive development in order to cope with environmental changes. Finally learning allows these circuits to memorize past events or adapt their response over time to improve their behavior. This thesis deals with the evolutionary mechanisms required to evolve these POEtic circuits. We argue that in order to fully realize the potential of POEtic circuits a novel evolutionary system that takes into account their characteristics and that encompasses both a genetic encoding and a developmental system is required. Indeed, evolutionary algorithms commonly used to evolve electronic circuits do not exploit the complex dynamics of development which is seen in biological organisms. They generally use a direct ge-