Arshinskiy L.V., Lebedev V.S Hypothesis contest for inductive inference based on non-strict probabilities // Informacionnye tehnologii i matematicheskoe modelirovanie v upravlenii slozhnymi sistemami: ehlektronnyj nauchnyj zhurnal [Information technology and mathematical modeling in the management of complex systems: electronic scientific journal], 2022. No. 4(16). P. 10-15. DOI: 10.26731/2658-3704.2022.4(16).10-15 [Accessed 17/12/22].
10.26731/2658-3704.2022.4(16).10-15
The paper describes a method for selecting hypotheses of the form "If ..., then..." from several alternatives obtained using the Bacon-Mill joint method of agreement and difference, in conditions when the relevant information is unreliable and/or contradictory. Sources of information can be well-structured arrays: spreadsheets, relational databases, etc. The methodology is based on the concept of non-strict probability, which follows from the vector representation of truth for VTF-logics. The choice of a specific hypothesis is proposed to be carried out using measures of certainty and reliability, known in VTF-logics and also used for non-strict probabilities.
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