Monte Carlo methods are mainly used in three problem classes: optimization, numerical integration, and generating draws from a probability distribution.
They are often used in physical and mathematical problems and are most useful when it is difficult or impossible to use other approaches.
The underlying concept is to use randomness to solve problems that might be deterministic in principle. Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. Please read the length guidelines and help move details into the article's body. This article's lead section may be too long.
