Reinforcement evolutionary learning using data mining algorithm with TSK-type fuzzy controllers

Reinforcement evolutionary learning using data mining algorithm (R-ELDMA) with a TSK-type fuzzy controller (TFC) for solving reinforcement control problems is proposed in this study. R-ELDMA aims to determine suitable rules in a TFC and identify suitable and unsuitable groups for chromosome selectio...

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Veröffentlicht in:	Applied soft computing Jg. 11; H. 3; S. 3247 - 3259
Hauptverfasser:	Hsu, Chi-Yao, Hsu, Yung-Chi, Lin, Sheng-Fuu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.04.2011
Schlagworte:	Association rules Control Fuzzy system R-ELDMA Reinforcement learning Symbiotic evolution Symbiotic evolution Fuzzy system Control Association rules R-ELDMA Reinforcement learning
ISSN:	1568-4946, 1872-9681
Online-Zugang:	Volltext
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