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Variational Genetic Programming for Optimal Control System Synthesis of Mobile Robots
Diveev A.I., Ibadulla S.I., Konyrbaev N.B., Shmalko E.Y.
The paper focuses on the problem of autonomous control system synthesis for the mobile robot
Variational Analytic Programming for Synthesis of Optimal Control for Flying Robot
Diveev A.I., Ibadulla S.I., Konyrbaev N.B., Shmalko E.Y.
on the quality of the chosen basic solution. An example of automatic control system synthesis for flying robot
Modeling tracks and controller for servosila engineer robot
Moskvin I., Lavrenov R.
in robotics. Models let our opportunity to make mistakes that could break real robot and learn
Synthesised Optimal Control for a Robotic Group by Complete Binary Genetic Programming*
Diveev A., Sofronova E., Prisca D.M.C.
The paper continues the study of symbolic regression methods for control learning. The optimal
Solving the Control Synthesis Problem Through Supervised Machine Learning of Symbolic Regression
Diveev A., Sofronova E., Konyrbaev N.
the control synthesis problem for a mobile robot using a supervised machine learning method. A relatively new
Collision avoidance system synthesis for a group of robots in unsupervised learning paradigm [Синтез системы разрешения коллизий для группы роботов в парадигме обучения без учителя]
Dotsenko A.V.
to robots. The control system which is responsible for collision avoidance is only activated when
Исследование методов машинного обучения на основе генетического программирования и символьной регрессии для управления мобильными роботами
Хайдер Ч.С., Каррар Ж.С., Флорес М.Н.
In recent decades, machine learning methods have become a key tool in the development and control
Using symbolic regression techniques for machine learning to control robot movement: Advantages and cons
Zhavush K.S., Chavush H.S., Mendez F.N.
into the application of symbolic regression in the domain of robot movement control, investigating both its advantages
Employing of RL Technology to Develop an Adaptive Motion Controller for a Line Follower Robot
Kim, T., Prakapovich, R.
follower robot. The controller learning process took place on the basis of the digital twin of the mobile
SELF-LEARNING OF AUTONOMOUS INTELLIGENT ROBOTS IN THE PROCESS OF SEARCH AND EXPLORE ACTIVITIES; [САМООБУЧЕНИЕ АВТОНОМНЫХ ИНТЕЛЛЕКТУАЛЬНЫХ РОБОТОВ В ПРОЦЕССЕ ПОИСКОВО-ИССЛЕДОВАТЕЛЬСКОЙ ДЕЯТЕЛЬНОСТИ∗]
Melekhin V.B., Khachumov V.M., Khachumov M.V.
-seeking behavior of robots. A self-learning algorithm has been developed for the conditions with a high level

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