Bayesian Optimization

A sequential optimization strategy for expensive black-box functions that builds a probabilistic surrogate model (Gaussian process) of the objective, then selects the next evaluation point by maximizing an acquisition function (EI, UCB). In robotics, Bayesian optimization is used for tuning controller gains, reward function parameters, and hyperparameters with minimal evaluations.