Monte Carlo methods

Some problems are simpler to solve empirically rather than theoretically. Monte Carlo methods use random simulations to find numerical answers to deterministic problems. Each simulation is independent and uses random initial conditions. For example, by placing random points inside a square and checking how many fall within the inscribed circle, one can estimate π from the resulting ratio. Monte Carlo methods are especially useful in risk analysis or system optimisation.