PROBABILISTIC INFERENCE FOR INTERVAL PROBABILITIES IN DECISION-MAKING PROCESSES

Authors

  • Oļegs Uzhga-Rebrov Information and Communication Technologies Research Centre, Rezekne Academy of Technologies (LV)
  • Galina Kuleshova Institute of Information Technology, Riga Technical University (LV)

DOI:

https://doi.org/10.17770/etr2019vol2.4112

Keywords:

Bayes’ formula, event indicators, interval probabilistic inference, interval probability, probability tree.

Abstract

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.

 

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Published

2019-06-20

How to Cite

[1]
O. Uzhga-Rebrov and G. Kuleshova, “PROBABILISTIC INFERENCE FOR INTERVAL PROBABILITIES IN DECISION-MAKING PROCESSES”, ETR, vol. 2, pp. 165–169, Jun. 2019, doi: 10.17770/etr2019vol2.4112.