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A credal network is a graphical representation for a set of joint probability distributions. In this paper we discuss algorithms for exact and approximate inferences in credal networks. We propose a branch-and-bound framework for inference, and focus on inferences for polytreeshaped networks. We also propose a new algorithm, A/R+, for outer approximations in polytree-shaped credal networks.doi:10.1016/j.ijar.2004.10.009 fatcat:xeulvzqdtbdk3i6rwsnl23fqxe