Complex cause-and-effect relationships

The paper discusses the task of constructing a logical inference of the specific property from data selected from a plurality of sets of source data. When solving the problem, it should be taken into account both the possibility of violating the cause-and-effect scheme due to noise and the possibility of not achieving the necessary conclusion. The cause-and-effect scheme of approximate inference has been built, consisting of objects of covering causes and consequences, which begins from the initial prerequisites and ends with the output of the object containing the required property. To describe the process of generating logical inference of the object with the property of interest from the source data, the concept of activating objects is introduced. This property allows one to represent the inference scheme in the form of a DAG (Directed Acyclic Graph). The simple algorithm for constructing the cause-and-effect scheme was built from the source data up to the object containing the desired property. This algorithm also determines the conditions for the existence of the ability to inference from the original conditions up to the object with the required property.