Acquisition Function

In Bayesian optimization, an acquisition function is a function that maps the posterior distribution of the objective function to a real number. The acquisition function is used to determine the next point at which to evaluate the objective function. The goal is to find the point that maximizes the acquisition function, which balances exploration (sampling points where the objective function is uncertain) and exploitation (sampling points where the objective function is expected to be high). Common acquisition functions include Probability of Improvement (PI), Expected Improvement (EI), and Upper Confidence Bound (UCB).
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