randomized algorithms

Randomized algorithms are a type of computational method that use random numbers to make decisions during their process. Instead of following a fixed path, these algorithms introduce randomness to potentially improve performance or simplify complex problems. For example, they may quickly find approximate solutions or efficiently search large datasets. While they don’t guarantee the same outcome every time, they can provide good results on average and are often easier or faster than traditional algorithms. Common applications include algorithms for sorting, searching, and even machine learning.