We consider multiple agents who's task is to determine the true state of a uncertain domain so they can act properly. If each agent only has partial knowledge about the domai...
As Bayesian networks become widely accepted as a normative formalism for diagnosis based on probabilistic knowledge, they are applied to increasingly larger problem domains. These...
Yanping Xiang, Kristian G. Olesen, Finn Verner Jen...
Abstract. Multiply sectioned Bayesian networks (MSBNs) were originally proposed as a modular representation of uncertain knowledge by sectioning a large Bayesian network (BN) into ...
Multiplysectioned Bayesian networks provide a probabilistic framework for reasoning about uncertain domains in cooperative multiagent systems. Several advances have been made in r...
Multiply sectioned Bayesian networks (MSBNs) provide a coherent and flexible formalism for representing uncertain knowledge in large domains. Global consistency among subnets in a...