29th International Conference on Computers Applications in Industry and Engineering

Modify Bayesian Network Structure with Inconsistent Constraints


This paper presents a theoretical framework and related methods for integrating probabilistic knowledge represented as low dimensional distributions (also called constraints) into an existing Bayesian network (BN), even when these constraints are inconsistent with the structure of the BN due to dependencies among relevant variables in the constraints being absent in the BN. Within this framework, a method has been developed to identify structural inconsistencies. Methods have also been developed to overcome such inconsistencies by modifying the structure of the existing BN.

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bayesian reasoning, knowledge representation

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