How neutral networks influence evolvability
Complexity
Neutral Networks and Evolvability with Complex Genotype-Phenotype Mapping
ECAL '01 Proceedings of the 6th European Conference on Advances in Artificial Life
Through the Labyrinth Evolution Finds a Way: A Silicon Ridge
ICES '96 Proceedings of the First International Conference on Evolvable Systems: From Biology to Hardware
Genotype-Phenotype-Mapping and Neutral Variation - A Case Study in Genetic Programming
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Resilient Individuals Improve Evolutionary Search
Artificial Life
An empirical investigation of how and why neutrality affects evolutionary search
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Finding needles in haystacks is harder with neutrality
Genetic Programming and Evolvable Machines
Genetic Programming and Evolvable Machines
Robustness and evolvability of recombination in linear genetic programming
EuroGP'13 Proceedings of the 16th European conference on Genetic Programming
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Whether neutrality has positive or negative effects on evolutionary search is a contentious topic, with reported experimental results supporting both sides of the debate. Most existing studies use performance statistics, e.g., success rate or search efficiency, to investigate if neutrality, either embedded or artificially added, can benefit an evolutionary algorithm. Here, we argue that understanding the influence of neutrality on evolutionary optimization requires an understanding of the interplay between robustness and evolvability at the genotypic and phenotypic scales. As a concrete example, we consider a simple linear genetic programming system that is amenable to exhaustive enumeration, and allows for the full characterization of these properties. We adopt statistical measurements from RNA systems to quantify robustness and evolvability at both genotypic and phenotypic levels. Using an ensemble of random walks, we demonstrate that the benefit of neutrality crucially depends upon its phenotypic distribution.