Interpretation problems: general mechanism and fundamental limitations of classical methods

Abstract

Purpose

The purpose of this paper is to investige the general computing mechanisms of solving the system information problems of interpretation and its fundamental limitations, due to physical basis Turing machine.

Design/methodology/approach

For creation of theoretical base of methodology, the authors make an attempt to demonstrate the possibility of a constructive building of Turing machine as meta-ontological basis of computing. In the course of this building the role of the operator of atomic implicative transition if-then as generic operator of recognition/decision-making is shown. In order to substantiate the thesis about the determinative role of implicative transition in the interpretation mechanisms, the authors will carry out the comparative analysis methods of interpretation in systems of pattern recognition and expert systems interpretation type.

Findings

The carried-out analysis allows to formulate a common mechanism underlying the classical methods of solving problems of interpretation and to concretize the fundamental limitations of these methods, caused computational basis of their actualization. The cybernetic interpretation of this mechanism is offered.

Originality/value

The fundamental limitations of classical methods of solving problems of interpretation sets the boundaries of the cybernetic approach and allows to outline a way out beyond it. In this context, the authors put forward knowledge-based mechanism of perceptual modeling of dynamics of system visual environment – autonomous agent.

Citation

Volchenkov, E. (2015), "Interpretation problems: general mechanism and fundamental limitations of classical methods", Kybernetes, Vol. 44 No. 5, pp. 692-704. https://doi.org/10.1108/K-02-2014-0038