Abstract: The subject of the research is the task of group management of autonomous agents in a dynamic multi-agent system and self-study of the management model. The author examines such aspects of the problem as a group interaction, using the example of the most effective group control algorithms, such as SWARM, ant algorithm, bee algorithm, firefly algorithm and fish school movement algorithm, and training of an artificial neural network through the use of reinforcement training. A comparison of various algorithms for finding the optimal path. The comparison was made on the basis of the gaming environment "Battlecode", which dynamically forms a new map for the new round, which ensured the quality of the comparison of the considered algorithms. The author uses statistical methods of data analysis, the selection and analysis of qualitative signs, forecasting methods, modeling method, classification method. The author shows that Q-learning increases its effectiveness by replacing the tabular representation of the Q-function with a neural network. This work proves the effectiveness of the bee algorithm in solving the problem of researching and patrolling the area. At the same time, the path search algorithm A* is much more flexible and efficient than the Dijkstra algorithm.

Abstract: The subject of the research is the problems of information security as well as development of the competitive strategy on the market of oil products for oil companies and implementation of the game theory method in the process of solving the aforesaid issues. Special attention is paid to the questions of providing information security. The author explaines the role of strategic interaction in the process of planning and developing company's competitive strategy. After that the author introduces the framework of the game theory in a form of a target function with a set game matrix which alllows to carry out simulation modeling when the actual basis is accumulated. The research methodology is based on the framework of the game theory, in particular, constant sum games, cooperative games and games with inexact information. The main conclusion of the research is the proof that it is possible to apply the game theory method to solving specific problems of oil industry. The author also offers to use the target function to fill in the game matrix for each problem and defines directions for further researches in this field using the game theory and simulation modeling methods.