Abstract
The problem of efficiency of general reasoning with knowledge updating on Bayesian networks is considered. The optimization should take into account not only the reasoning efficiency but also the prospective updating issues. An improved updating process based on an idea of data removing is proposed. Further possible improvement of the reasoning architecture is presented. Comparison of existing and proposed approaches are made on a basis of a computational experiment. Results of this experiment are presented.
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Łukaszewski, T. (2005). Comparison of Efficiency of Some Updating Schemes on Bayesian Networks. In: Kłopotek, M.A., Wierzchoń, S.T., Trojanowski, K. (eds) Intelligent Information Processing and Web Mining. Advances in Soft Computing, vol 31. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32392-9_38
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DOI: https://doi.org/10.1007/3-540-32392-9_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25056-2
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