Monte Carlo Simulation and Improvement of Variance Reduction Techniques

Variance Reduction Techniques in Monte Carlo Methods

Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the introduction of computers. This increased computer power has stimulated simulation analysts to develo...

Monte Carlo calculation of specific absorbed fractions: variance reduction techniques.

The purpose of the present work is to calculate specific absorbed fractions using variance reduction techniques and assess the effectiveness of these techniques in improving the efficiency (i.e. reducing the statistical uncertainties) of simulation results in cases where the distance between the source and the target organs is large and/or the target organ is small. The variance reduction techn...

Variance Reduction of Monte Carlo Simulation in Nuclear Engineering Field

The Monte Carlo method is a numerical technique that using random numbers and proba‐ bility to solve problems. It represents an attempt to model nature through direct simulation for any possible results, by substituting a range of values (a probability distribution) for any factor that has inherent uncertainty. The method is named after the city in the Monaco prin‐ cipality, because of roulette...

Monte Carlo Integration and Variance Reduction

Variance Reduction in Monte-Carlo Tree Search

Monte-Carlo Tree Search (MCTS) has proven to be a powerful, generic planning technique for decision-making in single-agent and adversarial environments. The stochastic nature of the Monte-Carlo simulations introduces errors in the value estimates, both in terms of bias and variance. Whilst reducing bias (typically through the addition of domain knowledge) has been studied in the MCTS literature...