Modus Ponens Generating Function in the Class of ^-valuations of Plausibility
Ildar Z. Batyrshin

TL;DR
This paper introduces a modus ponens generating function within the class of ^-valuations of plausibility, enabling inference procedures that handle ordinal uncertainty while maintaining strict monotonicity of conclusions.
Contribution
It proposes a new modus ponens generating function for ^-valuations of plausibility that preserves strict monotonicity in ordinal uncertainty inference.
Findings
The generating function operates based on linear ordering of plausibility values.
It ensures strict monotonicity of conclusions in inference procedures.
Applicable to ordinal scales of uncertainty.
Abstract
We discuss the problem of construction of inference procedures which can manipulate with uncertainties measured in ordinal scales and fulfill to the property of strict monotonicity of conclusion. The class of A-valuations of plausibility is considered where operations based only on information about linear ordering of plausibility values are used. In this class the modus ponens generating function fulfiling to the property of strict monotonicity of conclusions is introduced.
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Taxonomy
TopicsRough Sets and Fuzzy Logic · Multi-Criteria Decision Making · Bayesian Modeling and Causal Inference
