Automatic Modelling using Bayesian Networks for Explanation Generation
نویسندگان
چکیده
The task of generating informative explanations in industrial training involves automated formulation of system models with respect to the varying levels of the trainees' knowledge . Compositional 'Modeling provides a useful basis upon which to structure a suite of models that may reflect different complexities of the system being modelled . However, additional inferences are required in order to select appropriate model fragments to form a coherent system model that is suitable for a given trainee's degree of expertise . This paper presents a novel approach to perform such inferences by the use of Bayesian networks . The work is implemented and typical experimental results are given .
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تاریخ انتشار 2003