Unknown location targets searching system in known environment using reinforcement learning

Albrekht, Y.; Pysarenko, A.

Unknown location targets searching system in known environment using reinforcement learning

Файли

278920-643029-1-10-20230510.pdf (345.3 KB)

Дата

2023

Автори

Albrekht, Y.

Pysarenko, A.

Видавець

КПІ ім. Ігоря Сікорського

Анотація

This article investigates two different approaches to searching for objects of a certain type in a known environment: with a centrally controlled system using individual modules that transmit information and by dividing the entire search area into smaller ones and using individual objects. The article conducts experiments using reinforcement learning algorithms to compare the learning speed and capabilities of a system with search modules and centralized control and a separate object to search for static objects with random locations in a known environment and to search for objects moving at a constant speed in a known environment. The article provides detailed information about the experimental design, including the definition of the parameters for reinforcement learning and the size of the input and output data for the neural network. The results of the experiments are presented graphically, demonstrating the effectiveness of reinforcement learning and the difference in the learning speed and capabilities of the two systems under study.

Ключові слова

reinforcement learning, system of search modules, object detection

Бібліографічний опис

Albrekht, Y. Unknown location targets searching system in known environment using reinforcement learning / Y. Albrekht, A. Pysarenko // Адаптивні системи автоматичного управління : міжвідомчий науково-технічний збірник. – 2023. – № 1 (42). – С. 9-14. – Бібліогр.: 5 назв.