The article analyzes the emergence of the knowledge economy, development of the attention economy, the ability to measure the amount of knowledge. Particular attention is paid to the characteristics of the innovation environment, the problem of competitiveness, including the environment of fundamental science and higher education, as well as the formation of knowledge market as a special institution, significantly different from the traditional markets.

On the basis of the authors’ methodology, the models of productive potential of the Russian Federation regions, including estimations of intellectual capital, were constructed. It is shown that characteristics of well-being level and quality of life make a significant impact on the regional production’s efficiency. The characteristics of regions’ readiness to innovate are identified, it is possible to name it as a factor of production’s efficiency. It is shown that the inclusion of different factors of efficiency in the production potential model can significantly increase the differentiation of technical efficiency estimates, besides these estimates and their grades depend on a set of efficiency’s factors. On the basis of a comparison of real GRP and boundary GRP ratings, it is identified locally effective regions with a relatively high estimation of efficiency among regions with similar amounts of GRP and locally ineffective regions. It is calculated marginal effects of influence of the efficiency’s factors on the result of industrial activity in the region. It seems constructively to use these estimates while analyzing the prospects for regions’ development, which is based on the possibility of targeting impact on controllable efficiency’s factors. The article is also offered the option of methodology of the public policy efficiency estimation on the knowledge economy formation — an agent-based model for Russia, which is learning the “knowledge economy” sector and considering their relationship with the rest of the macroeconomic system.

To date, an extensive experience has been accumulated in investigation of problems related to quality, assessment of management systems, modeling of economic system sustainability. The performed studies have created a basis for development of a new research area — Economics of Quality. Its tools allow to use opportunities of model simulation for construction of the mathematical models adequately reflecting the role of quality in natural, technical, social regularities of functioning of the complex socio-economic systems. Extensive application and development of models, and also system modeling with use of supercomputer technologies, on our deep belief, will bring the conducted research of socio-economic systems to essentially new level. Moreover, the current scientific research makes a significant contribution to model simulation of multi-agent social systems and that is not less important, it belongs to the priority areas in development of science and technology in our country. This article is devoted to the questions of supercomputer technologies application in public sciences, first of all, — regarding technical realization of the large-scale agent-focused models (AFM). The essence of this tool is that owing to the power computer increase it has become possible to describe the behavior of many separate fragments of a difficult system, as socio-economic systems are. The article also deals with the experience of foreign scientists and practicians in launching the AFM on supercomputers, and also the example of AFM developed in CEMI RAS, stages and methods of effective calculating kernel display of multi-agent system on architecture of a modern supercomputer will be analyzed. The experiments on the basis of model simulation on forecasting the population of St. Petersburg according to three scenarios as one of the major factors influencing the development of socio-economic system and quality of life of the population are presented in the conclusion.

The research analyses the impact of the inequality of demographic transition on socio-demographic characteristics of the regional population and on the dynamics of these characteristics. The study was conducted with the help of computer-based experiments (simulations), which was run on the original agent-based model. The model is an artificial society, and personal characteristics of its members are set so that they could represent age-demographic structure of a simulate region. The agents are divided into two subgroups, which differ in their reproductive strategy. The first group has traditional strategy with high birth rate. The second group has considerably lower birth rate, observed in the modern developed societies. The model uses stochastic approaches to imitate the principle processes of population growth: mortality and morbidity. Mortality is set according to age-sex specific mortality coefficients, which do not differ across the population as a whole. New agents (child births) appear as a choice of agents – women of reproductive age, and the choice depends on the subgroup. The overall age and social structure of the region is aggregated across individual agents. A number of experiments has been carried out with the model utilization. This allowed forecasting the size and structure of the population of a given region. The results of the experiments have revealed that despite its simplicity, the developed agent-based model well predicts the initial conditions in the region (e.g. age-demographic and social structure). The model shows good fit in terms of estimating the dynamics of major characteristics of the population.