Monte Carlo Methods

A class of computational algorithms that use random sampling to obtain numerical results, typically for probability estimation or optimization. In robotics: Monte Carlo localization (particle filters) estimates robot pose; Monte Carlo tree search plans in stochastic environments; MC rollouts estimate expected returns in policy optimization.