Decomposition of belief function in hierarchical hypotheses space

It is shown that, in a hierarchically structured hypotheses space, any belief function whose focal elements are nodes in the hierarchy is a separable support function. An algorithm is proposed that decomposes such a separable support function into simple support functions. It is shown that the computational complexity of this decomposition algorithm is O(N²). Applications of the decomposition of separable support functions to the data fusion problem and the reasoning about control problem are discussed