Expanded Summary

The article discusses the issue of uncertainty, the role and importance of randomness in economic events. The essence of the deterministic-stochastic dualistic nature of these events, problems during modeling and possible directions for overcoming the contradictions are highlighted. Considerations about the ontological assumption and epistemological interpretation of the essence of randomness, ways of using deterministic nonlinear dynamic (multidimensional chaotic) and stochastic models in modeling economic processes are briefly reviewed. Even today, economic forecasting contributes to the development of the concept of economic development, solves the problems of economic growth in the conditions of limited natural, demographic, material and financial resources. Economic models, using mathematical apparatus, have the functions of classification and structuring of economic variables, including the identification of interrelationships and regularities, explaining the causes of events. Regardless of the need for many searches and new discoveries in the future, the attempt to bring economic science closer to the adequate fulfillment of the fundamental methodological function of science - its prognostic purpose - is increasingly gaining its rightful place among the Kantian "true sciences". In accordance with the dualistic philosophical tradition of free will and teleology, the inseparability of determinism (multidimensional chaos) and stochasticity will continue to be a topical subject of future nonlinear economic research. The specificity of scientific knowledge lies in its subjection to a number of strict principles (causation, truth, reliability, objectivity and relativity of scientific knowledge). Thus, in the cognitive process, methods ensuring the reliability of the obtained results are used. The path of the development of science clearly shows us that the results of scientific and cognitive activities are largely determined by the accuracy of the methods used. Today, in science, as well as in everyday life, cardinal changes are not only experienced by theories, but also by approaches and methods. Along with the development of computing techniques and the exponential growth in the creation and accumulation of big data, the "data-driven" approach is increasingly being used alongside the " theory-driven" approach. The further development and use of new research methods, approaches and tools (including artificial intelligence) is a necessary stage for obtaining important results in this direction, for the advancement of economic science. 

Keywords: economic planning, forecasting, foresight, dynamic models.