Mathematical modeling of systems, its nature and limits of applicability

Abstract

Purpose

The purpose of this paper is to establish the nature of mathematical modeling of systems within the framework of the object-semantic methodology.

Design/methodology/approach

The initial methodological position of the object-semantic approach is the principle of constructing concepts of informatics proceeding from fundamental categories and laws. As the appropriate foundation, this paper accepts the system-physical meta-ontology is being developed in this paper.

Findings

The genesis of system modeling is considered in the aspect of the evolution of language tools in the direction of objectification. A new conception of formalized knowledge is being put forward as the mathematical form of fixing time-invariant relations of the universe, reflecting regularity of the dynamics of natural or anthropogenic organization. Object knowledge is considered as a key component of the mathematical model, and the solving of system information problems with its use is characterized as “work of knowledge.” The establishment of the meta-ontological essence of modern mathematical modeling allows us to formulate its fundamental limitations.

Originality/value

The establishment of system-physical limitations of modern mathematical modeling outlines the boundaries from which it is necessary to proceed in the development of future paradigms of cognition of the surrounding world, which presuppose convergence, synthesis of causal (physicalism) and target (elevationism) determination.

Citation

Volchenkov, E. (2021), "Mathematical modeling of systems, its nature and limits of applicability", Kybernetes, Vol. 50 No. 9, pp. 2583-2596. https://doi.org/10.1108/K-06-2020-0393