Toward a Classification of Antagonistic Manifestations of Knowledge

As an accepted part of life, inconsistency is ubiquitous in knowledge, information and data. Inconsistency is a very important phenomenon and can be utilized as an effective tool to help accomplish the objectives in our endeavors. In this paper, we focus our attention on the logical forms in which antagonistic propositions (or inconsistent knowledge) manifest themselves in knowledge systems and how we quantify different antagonistic manifestations of knowledge. We describe algorithms that quantify twelve types of inconsistency that include: complementary, mutually exclusive, incompatible, anti-subsumption, anti-supertype, asymmetric, anti-inverse, mismatching, disagreeing, contradictory, precedence, and probabilistic value inconsistency. The take-home message is that there are circumstances in knowledge systems where inconsistencies arise in logical forms other than just a pair of complementary literals.