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The portfolio selection problem is treated as a two-player game: one player [Unit Investment Trust (UIT)] deals with investments, and the other (agent) allocates funds for it. The game is described in formal terms, and its solution is found. Note that the condition of sustainable development is derived directly from the game solution. UIT's learning is analyzed. Three possible statements of the UIT's learning problem are investigated, each corresponding to a particular machine learning model. An online learning model is considered to predict the information necessary for the agent's optimal behavior in the game. A computational experiment is provided: the three learning models are applied, and the simulation results are discussed. [ABSTRACT FROM AUTHOR]

This paper analyzes conditions of system compatibility in the game-theoretic models of resource allocation between social and private activities. We describe economic and administrative control mechanisms for system compatibility. [ABSTRACT FROM AUTHOR]

The problems of social networks analysis and calculation of the resulting opinions of network agents are considered. Algorithms for identifying strong subgroups and satellites as well as for calculating some quantitative characteristics of a network are implemented by the R programming language and tested on model examples. A new algorithm for calculating the resulting opinions of agents is developed by the R toolkit and tested on model examples. It is important that control actions that exert impact to the opinions should be applied exclusively to the members of strong subgroups (opinion leaders of a target audience), since they fully determine the stable resulting opinions of all network members. This approach allows saving control resources without significantly affecting its efficiency. Much attention is paid to the original models of optimal control (single subject) and conflict control (several competing subjects) under the assumption that the members of strong subgroups (opinion leaders) are already identified at the previous stage of network analysis. Models of optimal opinion control on networks are constructed and investigated by computer simulations using the author's method of qualitatively representative scenarios. Differential game-based models of opinion control on networks with budget constraints in the form of equalities and inequalities are constructed and analytically investigated. All used notions, approaches and results of this paper are interpreted in terms of marketing problems. [ABSTRACT FROM AUTHOR]