Distributed combination of belief functions

We consider the problem of combining belief functions in a situation where pieces evidence are held by agents at node communication network, and each agent can only exchange information with its neighbors. Using concept weight evidence, we propose distributed implementations Dempster’s rule cautious based, respectively, on average maximum consensus algorithms. also describe procedures whereby agree frame discernment list supported hypotheses, thus reducing amount data to be exchanged network. Finally, show feasibility robust combination procedure based implementation random sample (RANSAC) algorithm.