For single-objective optimization, new acquisition functions have been proposed to address noisy settings. The most widely used expected improvement (EI) acquisition function has been extended to noisy conditions, for example, expected quantile improvement (EQI) and augmented expected improvement (AEI) . Other acquisition functions that can intrinsically handle noise are information-based acquisition functions like predictive entropy search (PES) or Thompson sampling (TS) . Some other acquisition functions are risk-averse or based on knowledge gradient .