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Research questionHow can quality-diversity methods optimize behavioral diversity in arbitrary dissimilarity spaces?Quality-diversity methods must find high-quality solutions while covering behavioral variation. Domain-specific behavior descriptors can limit this process when solutions instead occupy arbitrary dissimilarity spaces, making diversity difficult to quantify and optimize generally.
Machine Learning
Neural and Evolutionary Computing
Latest papersRecent research connected to this question, newest first.Quality-diversity in dissimilarity spacesThe source develops a magnitude-based mathematical formulation for quality-diversity algorithms in generic dissimilarity spaces and demonstrates a general Go-Explore instantiation. The supplied evidence does not specify particular application domains or broader empirical limits.research paper · Sep 3, 2026
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