Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs
Kedar Hippalgaonkar,
Andre Low,
Flore Mekki-Berrada
et al.
Abstract:The development of automated high-throughput experimental platforms has enabled fast sampling of high-dimensional decision spaces. To reach target properties efficiently, these platforms are increasingly paired with intelligent experimental design. However, current optimizers show limitations in maintaining sufficient exploration/exploitation balance for problems dealing with multiple conflicting objectives and complex constraints. Here, we devised an Evolution-Guided Bayesian Optimization (EGBO) algorithm tha… Show more
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