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BŘEZINA, T., EHRENBERGER, Z., KRATOCHVÍL, C.
Original Title
Reinforcement learning model: control of nonlinear and unstable processes
Type
conference paper
Language
English
Original Abstract
Some experiences with using of the reinforcement learning model at control of nonlinear unstable processes are published in this paper. Control process is characterized by extensive depth in such cases, so the learning is computationally very demanding. We propose both using of nonlinear grid of the Q-function approximation table and also using of the learning conception “by expert observation“. Learning off (optimal) control policy is not based on blind searching a state space, but it is in progress with the help of further component, that is able to control the process. Problems are studied on active magnetic bearing one-mass model.
Keywords
control algorithm, Q-learning, neural network
Authors
RIV year
2002
Released
14. 6. 2001
Publisher
Institute of Termomechanics Academy of Sience of the Czech Republic, Prague 2001
Location
Svratka
ISBN
80-85918-64-1
Book
Inženýrská Mechanika 2001
Edition number
1
Pages from
40
Pages to
41
Pages count
2
BibTex
@inproceedings{BUT6259, author="Tomáš {Březina} and Zdeněk {Ehrenberger} and Ctirad {Kratochvíl}", title="Reinforcement learning model: control of nonlinear and unstable processes", booktitle="Inženýrská Mechanika 2001", year="2001", number="1", pages="2", publisher="Institute of Termomechanics Academy of Sience of the Czech Republic, Prague 2001", address="Svratka", isbn="80-85918-64-1" }