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Uncertainty in Artificial Intelligence
Current Bayesian net representations do not consider structure in the domain and include all variables in a homogeneous network. At any time, a human reasoner in a large domain may direct his attention to only one of a number of natural subdomains, i.e., there is 'localization' of queries and evidence. In such a case, propagating evidence through a homogeneous network is inefficient since the entire network has to be updated each time. This paper presents multiply sectioned Bayesian networksdoi:10.1016/b978-1-4832-8287-9.50052-9 fatcat:jk7quua6k5fb3jtxvicecmmzfu