Discrete Artificial Intelligence Problems and Number of Steps of Their Solution

摘要

Aggregate characteristics of discrete models appearing in different artificial intelligence problems are considered. It is shown that if an investigated object is a collection of its elements and its description contains properties of these elements and relations between them then a predicate calculus language is convinient for its simulation. In such a case a lot of problems are NP-hard. Upper bounds of steps for two essentially different decision algorithms are presented. A problem of transformation of an investigated object and the number of its decision steps is regarded. A many-level approach (consisting in the extraction of subformulas of goal conditions) to the decision of these problems is described. It allows to decrease the used time.