Review of Works by V. A. Yakubovich’s Scientific School on Artificial Intelligence and Robotics

Abstract

This is a review of the works of the research 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 emphasis is put on Yakubovich’s seminal works on machine learning and development of the concept of finitely convergent algorithms for solving recurrent objective inequalities. Typical results of their convergence are discussed in detail as a specific illustration. The study distinguishes the contribution of the school to the formation and development of modern theories of adaptive control and mathematical robotics, particularly, the theory of adaptive robots. A special section is devoted to adaptive suboptimal control.