An overview of works of the scientific school created by V. A. Yakubovich on the issues of artificial intelligence and robotics

The article presents an overview of the works of the scientific school of V. A. Yakubovich in the field of artificial intelligence, machine learning, adaptive systems, and robotics. The method of recurrent objective inequalities is considered in detail. The significance of the presented results for the further development of cybernetics and artificial intelligence is discussed. Special attention is given to seminal works of V. A. Yakubovich on machine learning and to the development of the concept of finitely converging algorithms for solving recurrent objective inequalities; some typical results on their convergence are discussed in detail for the sake of illustration. The paper distinctly highlights the contribution of the school to the formation and development of the modern theories of adaptive control and mathematical robotics, particularly the theory of adaptive robots. A special section is concerned with adaptive sub-optimal control.