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JOURNALS // Matematicheskoe modelirovanie // Archive

Mat. Model., 2020 Volume 32, Number 6, Pages 81–96 (Mi mm4190)

This article is cited in 4 papers

Discrete-dynamic modeling of governance for human capital

G. K. Kameneva, I. G. Kamenevab

a Dorodnicyn Computing Centre, FRC «Calculation and Control» of RAS
b FGAEI HE National research university «Higher school of economics»

Abstract: The article considers the problem of multi-criteria optimization of the state regulation of the quality of human capital in the information society. It describes human capital's dynamic by discrete model, taking into account the age dynamics of awareness and cognitive abilities of the individual as a carrier of information. Lifelong indices of human capital are constructed on the trajectories of human’s productivity and creativity, taking into account the increase in the quality of human capital in youth, and further, its decline in older age. The problem of state regulation is described as a bicriteria maximization of two population’s mathematical expectations of indices for the generation, taking into account not only the natural distribution of indices by starting values, but also the possibilities of socialization in the state-controlled education system. The identification of the model is based on the known population constraints on the phase tube of trajectories. The model is identified and researched by methods using approximation by Shannon’s metric nets. It is shown that the optimal choice of educational priorities by the state depends on the parameters of society: age mortality rates and the budget of time available for socialization of non-adults. There are combinations of parameters that lead to conflict of control criteria, so the solution is a set of Pareto-optimal strategies. For Russia, there is a dominant solution that prioritizes the development of cognitive abilities rather than awareness.

Keywords: human capital, cognitive abilities, socialization, education governance, information society, discrete dynamical model, multicriteria optimization, metric data analysis, Pareto-optimality, phase tube.

Received: 05.11.2019
Revised: 05.11.2019
Accepted: 23.12.2019

DOI: 10.20948/mm-2020-06-06


 English version:
Mathematical Models and Computer Simulations, 2021, 13:1, 144–153


© Steklov Math. Inst. of RAS, 2025