APPLICATION OF Q-leaning MACHINE LEARNING FOR THE FORMATION OF AN EFFECTIVE BEHAVIORAL STRATEGY FOR THE DEVELOPMENT OF INTELLECTUAL CAPITAL

Abstract

Goal. Evaluation of the intellectual capital of an enterprise, an organization that has many properties connected by appropriate relationships among themselves, which characterize the effectiveness of intellectual capital. Method. The following research methods were used to solve the set goal in the work: historical and empirical methods, the method of scientific abstraction, methods of analysis and synthesis, and the method of system analysis. The results. It is determined that the accumulation of capital of the efficiency of consumer or client capital owes to the capital of the strategy of attracting innovations of information potential and the choice of capital of alternatives and reproduces the increase in the level of organizational capital within the limits of its use. It was revealed that informational capital, which forms strategies for attracting informational potential, influences the choice of alternative capital and directly performs the main functions of forming and applying intellectual capital management mechanisms. In general, the capital of the strategy of attracting innovations of the information potential and the capital of alternatives directly performs the main functions of forming and applying the mechanisms of intellectual capital management in combination with other types of capital and independently of them. Scientific novelty. As a result of the research, the conceptual approach to the application of Q-leaning machine learning is substantiated in order to obtain the most effective strategy for the development of intellectual capital and increase the reliability of the obtained results. Practical significance. The study helps to increase the effectiveness of the development of intellectual capital development strategy and increase the reliability of the obtained results.