Due to an emergency, the following talk has been cancelled.
Title: Robustness and Evolvability in Evolutionary Computation
Speaker: Dr. Ting Hu, Assistant Professor, Department of Computer Science, Memorial University.
Robustness, the maintenance of a phenotypic character in the presence of genotypic changes, is the result of a redundant mapping between genotype and phenotype, where many mutational variants of a genotype produce an identical phenotype. Such robustness, at first glance, seems to hinder the capability of innovating, i.e. evolvability. However, empirical evidences have been reported on living organisms that robustness can facilitate evolvability since it allows genetic variants to expand in neutral spaces that provide a staging ground for future adaptive innovations. Redundant genotype to phenotype mapping is common in Evolutionary Computation. We use genotype networks to characterize the mutational connectivity of an Evolutionary Computation system, and to further quantify robustness and evolvability at the genotype, phenotype, and fitness levels. We show that robustness and evolvability correlate very differently at these three levels, and their interplay crucially depends on how the mutational connections are distributed among phenotypes.
Dr. Ting Hu is an Assistant Professor at the Department of Computer Science, Memorial University of Newfoundland. She was a postdoctoral researcher at Computational Genetics Laboratory, Dartmouth College. She obtained her PhD in Computer Science from Memorial University, MSc in Computer Science and BSc in Applied Mathematics from Wuhan University. Dr. Hu’s research interests include bio-inspired computing and bioinformatics.
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