title: Degeneracy: a design principle for achieving robustness and evolvability.
abstract: Robustness, the insensitivity of some of a biological system's functionalities to a set of distinct conditions, is intimately linked to fitness. Recent studies suggest that it may also play a vital role in enabling the evolution of species. Increasing robustness, so is proposed, can lead to the emergence of evolvability if evolution proceeds over a neutral network that extends far throughout the fitness landscape. Here, we show that the design principles used to achieve robustness dramatically influence whether robustness leads to evolvability. In simulation experiments, we find that purely redundant systems have remarkably low evolvability while degenerate, i.e. partially redundant, systems tend to be orders of magnitude more evolvable. Surprisingly, the magnitude of observed variation in evolvability can neither be explained by differences in the size nor the topology of the neutral networks. This suggests that degeneracy, a ubiquitous characteristic in biological systems, may be an important enabler of natural evolution. More generally, our study provides valuable new clues about the origin of innovations in complex adaptive systems.
authors.affiliation: Defence and Security Applications Research Centre, University of New South Wales at the Australian Defence Force Academy, Canberra, Australia. j.whitacre@adfa.edu.au
authors.forename: James
authors.initials: J
authors.lastname: Whitacre
authors.forename: Axel
authors.initials: A
authors.lastname: Bender
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D019143:Evolution, Molecular; D053263:Gene Regulatory Networks; D005828:Genetics, Population; D005838:Genotype; D006801:Humans; D008954:Models, Biological; D008957:Models, Genetic; D015233:Models, Statistical; D016571:Neural Networks, Computer; D010641:Phenotype; D012641:Selection, Genetic; D012984:Software