Approximate syllogism as argumentative expression for knowledge representation and reasoning with Generalized Bayes' Theorem

We propose an argumentative equivalent model for the Generalized Bayes’ Theorem (GBT) that is based on syllogisms. In the model, probability values in the GBT are expressed as quantified statements "Q A are B”, conditional probabilities as the premises of the argument and the variable to be estimated as the conclusion. Application of GBT is performed equivalently by resolving the syllogism, thus providing non-specialized users with an interpretable equivalent model of GBT.

keywords: approximate syllogism, approximate reasoning, fuzzy reasoning, Generalized Bayes Theorem