Přístupnostní navigace
E-application
Search Search Close
Publication detail
BŘEZINA, T., KREJSA, J., VĚCHET, S.
Original Title
STOCHASTIC POLICY IN Q-LEARNING USED FOR CONTROL OF AMB
English Title
Type
conference paper
Language
Czech
Original Abstract
A great intention is lately focused on Reinforcement Learning (RL) methods. The article is focused on improving model free RL method known as Q-learning algorithm used on active magnetic bearing (AMB) model. Stochastic strategy and adaptive integration step increased the speed of learning approximately hundred times. Impossibility of using proposed improvement online is the only drawback, however it might be used for pretraining on simulation model and further fined online.
English abstract
Keywords
Reinforcement Learning, Q-learning, Active Magnetic Bearing
Key words in English
Authors
RIV year
2002
Released
13. 5. 2002
Publisher
Institute of Mechanics of Solids, Faculty of Mechanical Engineering, Brno University of Technology
Location
Brno
ISBN
80-214-2109-6
Book
Inženýrská mechanika 2002
Edition number
1
Pages from
7
Pages to
8
Pages count
2
BibTex
@inproceedings{BUT9663, author="Tomáš {Březina} and Jiří {Krejsa} and Stanislav {Věchet}", title="STOCHASTIC POLICY IN Q-LEARNING USED FOR CONTROL OF AMB", booktitle="Inženýrská mechanika 2002", year="2002", number="1", pages="2", publisher="Institute of Mechanics of Solids, Faculty of Mechanical Engineering, Brno University of Technology", address="Brno", isbn="80-214-2109-6" }