Monte Carlo integration

Monte Carlo integration is a technique for numerical integration that uses random numbers. It is a particular Monte Carlo method that numerically computes a definite integral. Where most other numerical integration algorithms evaluate the integrand at the points of a regular grid, Monte Carlo integration chooses the evaluation points at random. This makes it especially useful for higher-dimensional integrals, where grid-based rules need an impractical number of points. The lead names several ways of carrying it out, including uniform sampling, stratified sampling, importance sampling, sequential Monte Carlo (also known as a particle filter), and mean-field particle methods.