No abstract

The article discusses the issues of logical inference for abnormal truth-values of premises in logics with vector semantics from the VTF-logic class. Such situations as strict lies, uncertainty, and complete contradiction are considered in this article. It is shown that the truth of the conclusion in this case can take an interval value and the nature of this interval is preserved throughout the inference. This feature can be used to detect knowledge base artefacts during dynamic verification of knowledge bases.

The paper is devoted to the problem of expert systems knowledge bases verification. The methodological basis of verification is logics with vector semantics in the VTF-logics form. The knowledge model is a rule-based system. The issues of algorithmization of contradictions and other problems detection are considered in the paper. Algorithmization is based on the characteristic features of in VTF-logics inference. It is shown that in the formalism under consideration, the anomalous truth of a small premise generates the same conclusion (a large premise is considered strictly true). Anomalies such as falsity, uncertainty, and contradiction are considered. The problems of reducing the computational complexity of algorithms are considered.