  Reverse Monte Carlo (RMC) is an algorithm that incorporates stochastic
modification of the action as part of the process that updates the fields in a
Monte Carlo simulation. Such update moves have the potential of lowering or
eliminating potential barriers that may cause inefficiencies in exploring the
field configuration space. The highly successful Cluster algorithms for spin
systems can be derived from the RMC framework. In this work we apply RMC ideas
to pure gauge theory, aiming to alleviate the critical slowing down observed in
the topological charge evolution as well as other long distance observables. We
present various formulations of the basic idea and report on our numerical
experiments with these algorithms.
