Implementation of Formula Partial Sequence for Rough Solution of AI Problems in the Framework of the Logic-Predicate Approach

Abstract

The paper is the answer to the question posed to the author during a report at the CSIT-2017 conference: whether it is possible to change a logic-predicate network so that not only objects with descriptions from the training set are recognized, but also differ slightly from them. The notion of partial sequence of a predicate formula, introduced by the author earlier, makes it possible to change the content of network cells so that the degree of similarity of a recognizable object fragment to fragments of objects from the training set, and then the degree of certainty that the object belongs to a given class, is calculated. A brief description of the logic-predicate approach to AI problems, the information about a logic-predicate network, the notion of partial sequence are presented in the paper.