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Reinforcement Learning for Model Problems of Optimal Control
- Authors: Semenov S.S.1, Tsurkov V.I.2
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Affiliations:
- Moscow Institute of Physics and Technology, 141701, Dolgoprudny, Moscow Oblast, Russia
- Federal Research Center “Computer Science and Control,” Russian Academy of Sciences, 119333, Moscow, Russia
- Issue: No 3 (2023)
- Pages: 76-89
- Section: ARTIFICIAL INTELLIGENCE
- URL: https://journal-vniispk.ru/0002-3388/article/view/136878
- DOI: https://doi.org/10.31857/S0002338823030125
- EDN: https://elibrary.ru/EVAFAM
- ID: 136878
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Abstract
The functionals of dynamic systems of various types are optimized using modern methods of reinforcement learning. The linear resource allocation problem, as well as the optimal consumption problem and its stochastic modifications are considered. In the reinforcement learning strategy gradient methods are used.
About the authors
S. S. Semenov
Moscow Institute of Physics and Technology, 141701, Dolgoprudny, Moscow Oblast, Russia
Email: semenov.ss@phystech.edu
Россия, МО, Долгопрудный
V. I. Tsurkov
Federal Research Center “Computer Science and Control,” Russian Academy of Sciences, 119333, Moscow, Russia
Author for correspondence.
Email: tsur@ccas.ru
Россия, Москва
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