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Q-Learning: From Discrete to Continuous Representation
. The method used suitable approximator to replace the discrete table. We choose local approxiimator called Locally Weighted Regression (LWR) (Atketson &Moore & Shaal, 1996) fromQ-learning standard algorithm is res...
BC - Teorie a systémy řízení
- 2004 •
- Jx
Rok uplatnění
Jx - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
NONLINEAR CONTROLLER OF ACTIVE MAGNETIC BEARING
compensator learned by control error. Compensator is constituted by automatic approximator based on one of the Locally Weighted Learning methods. Second approach is control (parameter) values come from actions of ...
JD - Využití počítačů, robotika a její aplikace
- 2005 •
- C
Rok uplatnění
C - Kapitola v odborné knize
Inverted modelling with approximation methods
This paper deals with making the inverse kinematic modells. Two robotic pedal mechanisms are used as examples of the modelling process. The Neurofuzzy approach, the Lazy Learning method, the Locally Weighted Regression and ...
JD - Využití počítačů, robotika a její aplikace
- 2003 •
- D
Rok uplatnění
D - Stať ve sborníku
Continuous Q-learning application
be used, with respect to memory and computational requirements the local approximator is particularrly favorable. We have used Locally Weighted Regression (LWR) algorithm. The paperStandard algorithm of Q-Learning...
BC - Teorie a systémy řízení
- 2004 •
- D
Rok uplatnění
D - Stať ve sborníku
NONLINEAR PREDICTIVE CONTROLLER WITH LOCAL APPROXIMATOR FOR ACTIVE MAGNETIC BEARING
predictive compensation, realized by local automatic approximator, which is presented further. Local approximator repeatedly uses the locally linear model based on algorithm of locally weighted regression...
JD - Využití počítačů, robotika a její aplikace
- 2005 •
- Jx
Rok uplatnění
Jx - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
Using Q-Learning with LWR in continuous space
Locally Weighted Learning (LWR) is a class of approximations, based on a local model. In this paper we demonstrate using LWR together with Q-learning for control tasks. Q-learning is the most effe...
BC - Teorie a systémy řízení
- 2003 •
- D
Rok uplatnění
D - Stať ve sborníku
Using Modified Q-learning With LWR for Inverted Pendulum Control
Locally Weighted Learning (LWR) is a class of approximations, based on a local model. In this paper we demonstrate using LWR together with Q-learning for control tasks. Q-learning is the most effe...
BC - Teorie a systémy řízení
- 2003 •
- D
Rok uplatnění
D - Stať ve sborníku
Using Modified Q-learning With LWR for Inverted Pendulum Control
Locally Weighted Learning (LWR) is a class of approximations, based on a local model. In this paper we demonstrate using LWR together with Q-learning for control tasks. Q-learning is the most effe...
BC - Teorie a systémy řízení
- 2003 •
- D
Rok uplatnění
D - Stať ve sborníku
The Behavior of LWPR Method on Approximation of Multivariable Functions
Locally Weighted Projection Regression is an incremental approximation method used in real-time control. It was developed to approximate functions with high-dimensional inputs. When used for problems with multivariable outputs, this...
JD - Využití počítačů, robotika a její aplikace
- 2005 •
- D
Rok uplatnění
D - Stať ve sborníku
Robustness of Supervised Learning Based on Combined Centroids
and a subsequent optimization of their weights, is illustrated on the task of localizingRecently, we proposed a novel sparse centroid-based supervised learning method, allowing to optimize a single centroid and its corresp...
Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
- 2021 •
- D •
- Link
Rok uplatnění
D - Stať ve sborníku
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