Bayesian optimization algorithms

Bayesian optimization is a method for finding the best solution to a problem efficiently by using past information. It builds a probabilistic model of how different choices perform, then uses this model to predict where better options might be. This helps it decide which options to try next, balancing exploring new possibilities and exploiting known good ones. It's useful when evaluating options is costly or time-consuming, such as tuning complex machine learning models or engineering designs. Overall, it intelligently guides the search process to find optimal solutions with fewer experiments or evaluations.