The advantage of Beam Search is that it is computationally efficient, but the disadvantage is that it may miss some paths that are not so obvious, but may ultimately be better. Lookahead Search: An extension based on Beam Search It not only considers the optimal solution of the current step when searching, but also looks ahead multiple steps to consider future possibilities. This search strategy can help the algorithm make longer-term decisions, but the computational cost will also increase.The key to Lookahead Search is that it attempts to predict and evaluate different decision paths in order to select the optimal course of action.
MCTS: A heuristic search algorithm for certain brazil email list types of decision-making processes that combines stochastic simulation and decision tree search. MCTS evaluates different decision paths through multiple simulations and selects the optimal action based on the results of these simulations. MCTS is particularly well-suited for two-player zero-sum games such as Go, chess, etc. It explores all possible paths of action by constructing the entire tree and evaluates these paths through the simulation. . Bootstrap This is a resampling technique used to generate a new set of samples from the original data set to estimate the distribution of a statistic (such as the mean, variance, etc.
). This method allows the uncertainty and stability of model parameters to be estimated without making any assumptions about the overall distribution. The steps of the bootstrap method typically include: randomly extracting samples from the original data set, allowing for repeated sampling (that is, calculating the required statistic based on the extracted samples multiple times (usually thousands); times), to obtain a distribution of the statistic, using this distribution to estimate the standard error, confidence intervals, or other characteristics of the original statistic. In the field of machine learning, the bootstrap method can be used to improve the generalization ability and robustness of a model.