InfoMax Bayesian learning of the Furuta pendulum

Jeni László A. and Flórea György and Lőrincz András: InfoMax Bayesian learning of the Furuta pendulum. In: Acta cybernetica, (18) 4. pp. 637-649. (2008)

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Abstract

We have studied the InfoMax (D-optimality) learning for the two-link Furuta pendulum. We compared InfoMax and random learning methods. The InfoMax learning method won by a large margin, it visited a larger domain and provided better approximation during the same time interval. The advantages and the limitations of the InfoMax solution are treated.

Item Type: Article
Journal or Publication Title: Acta cybernetica
Date: 2008
Volume: 18
Number: 4
ISSN: 0324-721X
Page Range: pp. 637-649
Language: English
Place of Publication: Szeged
Event Title: Symposium of Young Scientists on Intelligent Systems (2.) (2007) (Budapest)
Related URLs: http://acta.bibl.u-szeged.hu/38526/
Uncontrolled Keywords: Számítástechnika, Kibernetika
Additional Information: Bibliogr.: p. 648-649. ; összefoglalás angol nyelven
Subjects: 01. Natural sciences
01. Natural sciences > 01.02. Computer and information sciences
Date Deposited: 2016. Oct. 15. 12:25
Last Modified: 2022. Jun. 16. 15:02
URI: http://acta.bibl.u-szeged.hu/id/eprint/12839

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