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.

中文翻译：

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VA Yakubovich 科学学院关于人工智能和机器人技术的著作回顾

摘要

这是对 VA Yakubovich 研究学院在人工智能、机器学习、自适应系统和机器人领域的工作的回顾。详细考虑了经常性客观不平等的方法。讨论了所提出的结果对于控制论和人工智能进一步发展的意义。特别强调雅库博维奇在机器学习和开发用于解决经常出现的客观不平等问题的有限收敛算法概念方面的开创性著作。作为具体说明，详细讨论了它们收敛的典型结果。该研究突出了该学派对现代自适应控制和数学机器人理论，特别是自适应机器人理论的形成和发展的贡献。有一个专门的部分专门讨论自适应次优控制。