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rdf:type
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Description
| - 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 wiith the help of further component, that is able to control the process. Problems are studied on active magnetic bearing one-mass model.
- 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 wiith the help of further component, that is able to control the process. Problems are studied on active magnetic bearing one-mass model. (en)
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Title
| - Reinforcement learning model: control of nonlinear and unstable processes
- Reinforcement learning model: control of nonlinear and unstable processes (en)
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skos:prefLabel
| - Reinforcement learning model: control of nonlinear and unstable processes
- Reinforcement learning model: control of nonlinear and unstable processes (en)
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skos:notation
| - RIV/00216305:26210/01:PU23020!RIV/2003/GA0/262103/N
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http://linked.open.../vavai/riv/strany
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/00216305:26210/01:PU23020
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - control algorithm, Q-learning, neural network (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...ontrolniKodProRIV
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http://linked.open...v/mistoKonaniAkce
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http://linked.open...i/riv/mistoVydani
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http://linked.open...i/riv/nazevZdroje
| - Inženýrská Mechanika 2001
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...ocetUcastnikuAkce
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http://linked.open...nichUcastnikuAkce
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http://linked.open...vavai/riv/projekt
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http://linked.open...UplatneniVysledku
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http://linked.open...iv/tvurceVysledku
| - Březina, Tomáš
- Kratochvíl, Ctirad
- Ehrenberger, Zdeněk
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http://linked.open...vavai/riv/typAkce
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http://linked.open.../riv/zahajeniAkce
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number of pages
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http://purl.org/ne...btex#hasPublisher
| - Ústav termomechaniky AV ČR
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https://schema.org/isbn
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http://localhost/t...ganizacniJednotka
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