  A conceptual foundation for approximation of belief functions is proposed and
investigated. It is based on the requirements of consistency and closeness. An
optimal approximation is studied. Unfortunately, the computation of the optimal
approximation turns out to be intractable. Hence, various heuristic methods are
proposed and experimantally evaluated both in terms of their accuracy and in
terms of the speed of computation. These methods are compared to the earlier
proposed approximations of belief functions.
