Evolvability of representations in complex system engineering: A survey

A successful design optimization crucially depends on the underlying representation, which has to adapt to a variety of demands and changing boundary conditions. Complex system engineering addresses these challenges through key features like self-organization, modularity, locality, or evolution. The representation covers the parameter setup (location and quantity) and the mapping between parameter space (genotype) and design space (phenotype), and should allow for both adaptation and specialization of a design. To quantify the potential of a representation, suitable quality criteria are needed. Evolvability is such a criterion, which has been derived from biological analysis. However, many biological and technical studies propose different definitions of evolvability. We analyze, interpret, and extend them in order to derive an evolvability criterion suitable for complex system engineering. This can be used as a basis for future design optimization problems.