Quality-diversity in dissimilarity spaces
Annual Conference on Genetic and Evolutionary Computation (GECCO), 2022
Abstract
The theory of magnitude provides a mathematical framework for quantifying and maximizing diversity. We apply this framework to formulate quality-diversity algorithms in generic dissimilarity spaces. In particular, we instantiate and demonstrate a very general version of Go-Explore with promising performance.
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