Belief updating in multiply sectioned Bayesian networks without repeated local propagations
نویسندگان
چکیده
منابع مشابه
Belief updating in multiply sectioned Bayesian networks without repeated local propagations
Multiply sectioned Bayesian networks (MSBNs) provide a coherent and flexible formalism for representing uncertain knowledge in large domains. Global consistency among subnets in a MSBN is achieved by communication. When a subnet updates its belief with respect to an adjacent subnet, existing inference operations require repeated belief propagations (proportional to the number of linkages betwee...
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We redeene inference operations for multiply sectioned Bayesian networks (MS-BNs). When two adjacent subnets exchange belief, previous operations require repeated belief propagations within the receiving subnet. The new operations require such propagation only twice. We prove that the new operations do not compromise the coherence while improving the eeciency. A MSBN must be initialized before ...
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Recent developments show that Multiply Sectioned Bayesian Networks (MSBNs) can be used for diagnosis of natural systems as well as for model-based diagnosis of artificial systems. They can be applied to single-agent oriented reasoning systems as well as multiagent distributed reasoning systems. Belief propagation between a pair of subnets plays a central role in maintenance of global consistenc...
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Recent developments show that Multiply Sectioned Bayesian Networks (MSBNs) can be used for diagnosis of natural systems as well as for model-based diagnosis of artiicial systems. They can be applied to single-agent oriented reasoning systems as well as multi-agent distributed probabilistic reasoning systems. Belief propagation between a pair of subnets in a MSBN plays a central role in maintena...
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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 domain and local observation how can agents accomplish the task with the least amount of commu nication Multiply sectioned Bayesian networks MSBNs provide an e ective and exact framework for such a task but also impose a set of c...
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ژورنال
عنوان ژورنال: International Journal of Approximate Reasoning
سال: 2000
ISSN: 0888-613X
DOI: 10.1016/s0888-613x(99)00030-4