  Methods for the reduction of the complexity of computational problems are
presented, as well as their connections to renormalization, scaling, and
irreversible statistical mechanics. Several statistically stationary cases are
analyzed; for time dependent problems averaging usually fails, and averaged
equations must be augmented by appropriate memory and random forcing terms.
Approximations are described and examples are given.
