Probabilistic Inference for Interval Probabilities in Decision-Making Processes
Environment. Technology. Resources: Proceedings of the 12th International Scientific and Practical Conference. Vol.2 2019
Oleg Uzhga-Rebrov, Gaļina Kuļešova

The present paper considers one approach to Bayes’ formula based probabilistic inference under interval values of relevant probabilities; the necessity of it is caused by the impossibility to obtain reliable deterministic values of the required probabilistic evaluations. The paper shows that the approach proves to be the best from the viewpoint of the required amount of calculations and visual representation of the results. The execution of the algorithm of probabilistic inference is illustrated using a classical task of decision making related to oil mining. For visualisation purposes, the state of initial and target information is modelled using probability trees.


Keywords
Bayes’ formula, event indicators, interval probabilistic inference, interval probability, probability tree
DOI
10.17770/etr2019vol2.4112
Hyperlink
http://journals.ru.lv/index.php/ETR/article/view/4112

Uzhga-Rebrov, O., Kuļešova, G. Probabilistic Inference for Interval Probabilities in Decision-Making Processes. In: Environment. Technology. Resources: Proceedings of the 12th International Scientific and Practical Conference. Vol.2, Latvia, Rēzekne, 20-22 June, 2019. Rēzekne: Rēzeknes Tehnoloģiju akadēmija, 2019, pp.165-169. ISSN 1691-5402. e-ISSN 2256-070X. Available from: doi:10.17770/etr2019vol2.4112

Publication language
English (en)
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