Stochastic simulation algorithms and methods were initially developed to analyse chemical reactions involving large numbers of species with complex reaction kinetics.

Numerically, the Gillespie algorithm or stochastic simulation algorithm is often used to create realisations of stochastic cellular processes, from which statistics can be calculated.

A pop-up Java web applet with fast simulation algorithms and a large library of interesting Life patterns.

The simulation algorithm of DEVS models considers two issues: time synchronization and message propagation.

Partial-propensity direct method, a stochastic simulation algorithm for chemical reaction networks; a variant of the Gillespie algorithm.

This idea can be implemented with a fast run-time thermal simulation algorithm at architectural level.

Other simulation techniques (such as replica exchange) are supported through a plug-in-based infrastructure, which also allows users to develop their own simulation algorithms and models.

Given an atomic DEVS model, simulation algorithms are methods to generate the model's legal behaviors which are trajectories not to reach to illegal states.

Interactive vector slime implementations can also eventually be found in computer games as a substitute for a more correct physical simulation algorithm.

As a result, the posterior distribution is difficult to calculate, even using standard simulation algorithms (e.g. Gibbs sampling).