Synthesis of Solutions under Uncertainties in DistributedExpert

The synthesis of solutions under uncertainties is one of the key issues for cooperation among expert systems in a distributed expert system. In this paper, we present a model to synthesise solutions from diierent expert systems in a horizontal cooperation. Firstly, we use a conditioning belief function as an approach to ego-modify belief. Then, we use a Boolean algebra hypothesis space to represent the uniform frame of discernment in the model. Last, we propose a synthesis mapping which is a generalization of probabilistic mapping. This mapping can synthesize all uncertainty information encoded by probability functions or mass functions.