In this exercise, we$$ll explore different types of randomized algorithms. We say that a randomized algorithm is a Las Vegas algorithm if it is always correct $($that is$,$ it returns the right answer with probability $1),$ but the running time is a random variable. We say that a randomized algorithm is a Monte Carlo algorithm if there is some probability that it is incorrect. For example, QuickSort $($with a random pivot$)$ is a Las Vegas algorithm, since it always returns a sorted array, but it might be slow if we get very unlucky.

To get more insight on randomized algorithms, we will revisit the problem of finding an experienced dogwalker from a group where the majority are experienced. You may assume WalkAndRate runs in O$(1),$ and that isExperienced is a correct algorithm.