A new quality-diversity algorithm uses CMA-ES to optimize per-cell hypervolume improvements against lagging threshold fronts, beating or matching prior methods on four multi-objective domains.
Two-dimensional subset selection for hypervolume and epsilon-indicator
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Multi-Objective Covariance Matrix Adaptation MAP-Annealing
A new quality-diversity algorithm uses CMA-ES to optimize per-cell hypervolume improvements against lagging threshold fronts, beating or matching prior methods on four multi-objective domains.