An Expert System for Decision Making in the Face of Imprecise, Inconsistent and Paracomplete Data – Metaverse Security Application Using DLP

With the advancement of numerous applications of AI techniques, in situations involving imprecision or uncertainty, experts may issue inaccurate, conflicting opinions or omit information. The usual systems based on classical reasoning to manipulate such data show us difficulty in implementation or their logical analysis. Even decision-makers are not comfortable with the presence of inaccurate information. This work presents an expert system that allows manipulating data from databases with imprecise, inconsistent, or incomplete information. Such a system is based on a new class of non-classical logic, the paraconsistent annotated evidential logic Eτ, which allows working with the concepts mentioned earlier to provide a more reliable decision to the decision maker.